Index (io.github.ddolib-cetic-ucl:ddolib 0.0.6 API)

A B C D E F G H I J K L M N O P Q R S T U V W
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

AcsModel<T> - Interface in org.ddolib.modeling: Defines the structure of an optimization model solved using the Anytime Column Search (ACS) algorithm within the Decision Diagram Optimization (DDO) framework.
ACSSolver<T> - Class in org.ddolib.acs.core.solver: Implementation of an Anytime Column Search (ACS) solver for decision diagram-based optimization problems.
ACSSolver(AcsModel<T>) - Constructor for class org.ddolib.acs.core.solver.ACSSolver: Constructs an ACS solver with all required and optional components provided via an AcsModel.
aircraftClass - Variable in class org.ddolib.examples.alp.ALPDecision: The class of the aircraft being assigned.
aircraftClass - Variable in class org.ddolib.examples.alp.ALPProblem: Mapping of each aircraft to its class.
aircraftDeadline - Variable in class org.ddolib.examples.alp.ALPProblem: Deadline for each aircraft.
aircraftTarget - Variable in class org.ddolib.examples.alp.ALPProblem: Target landing time for each aircraft.
ALPAcsMain - Class in org.ddolib.examples.alp: Aircraft Landing Problem (ALP) with Acs.
ALPAcsMain() - Constructor for class org.ddolib.examples.alp.ALPAcsMain
ALPAstarMain - Class in org.ddolib.examples.alp: Aircraft Landing Problem (ALP) with AsTar.
ALPAstarMain() - Constructor for class org.ddolib.examples.alp.ALPAstarMain
ALPDdoMain - Class in org.ddolib.examples.alp: Aircraft Landing Problem (ALP) with Ddo.
ALPDdoMain() - Constructor for class org.ddolib.examples.alp.ALPDdoMain
ALPDecision - Class in org.ddolib.examples.alp: Represents a decision in the Aircraft Landing Problem (ALP).
ALPDecision(int, int) - Constructor for class org.ddolib.examples.alp.ALPDecision: Constructs a new decision assigning an aircraft of the given class to the given runway.
ALPFastLowerBound - Class in org.ddolib.examples.alp: Fast lower bound computation for the Aircraft Landing Problem (ALP).
ALPFastLowerBound(ALPProblem) - Constructor for class org.ddolib.examples.alp.ALPFastLowerBound: Constructs a new fast lower bound evaluator for the given ALP problem.
ALPLnsMain - Class in org.ddolib.examples.alp: Entry point for solving the Aircraft Landing Problem (ALP) using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
ALPLnsMain() - Constructor for class org.ddolib.examples.alp.ALPLnsMain
ALPProblem - Class in org.ddolib.examples.alp: Represents the Aircraft Landing Problem (ALP).
ALPProblem(int, int, int, int[], int[], int[], int[][]) - Constructor for class org.ddolib.examples.alp.ALPProblem: Constructs an ALP problem without specifying an optimal value.
ALPProblem(int, int, int, int[], int[], int[], int[][], Optional<Double>) - Constructor for class org.ddolib.examples.alp.ALPProblem: Constructs an ALP problem with the specified parameters.
ALPProblem(String) - Constructor for class org.ddolib.examples.alp.ALPProblem: Constructs an ALP problem by reading from a file.
ALPRanking - Class in org.ddolib.examples.alp: Ranking heuristic for ALPState objects in the Aircraft Landing Problem (ALP).
ALPRanking() - Constructor for class org.ddolib.examples.alp.ALPRanking
ALPRelax - Class in org.ddolib.examples.alp: Relaxation operator for ALPState in the Aircraft Landing Problem (ALP).
ALPRelax(ALPProblem) - Constructor for class org.ddolib.examples.alp.ALPRelax: Constructs a relaxation operator for the given ALP problem.
ALPState - Class in org.ddolib.examples.alp: Represents the state of the Aircraft Landing Problem (ALP) at a given moment.
ALPState(int[], RunwayState[]) - Constructor for class org.ddolib.examples.alp.ALPState: Constructs a new ALP state with the given remaining aircraft and runway states.
ALPState(ALPState) - Constructor for class org.ddolib.examples.alp.ALPState: Copy constructor: creates a deep copy of another ALPState.
ArraysUtil - Class in org.ddolib.util: Utility class providing common array-related operations.
ArraysUtil() - Constructor for class org.ddolib.util.ArraysUtil
AStarSolver<T> - Class in org.ddolib.astar.core.solver
AStarSolver(Model<T>) - Constructor for class org.ddolib.astar.core.solver.AStarSolver
AwAstarModel<T> - Interface in org.ddolib.modeling: Defines the structure of an optimization model solved using the Anytime Weighted A* (AWA*) algorithm within the Decision Diagram Optimization (DDO) framework.
AwAstarSolver<T> - Class in org.ddolib.awastar.core.solver: Implementation of an Anytime Weighted A* search (AWA*) solver for decision diagram-based optimization problems.
AwAstarSolver(AwAstarModel<T>) - Constructor for class org.ddolib.awastar.core.solver.AwAstarSolver: Constructs a solver via a AwAstarModel.

B

best - Variable in class org.ddolib.ddo.core.mdd.Node: The edge terminating the longest path to this node.
best() - Method in class org.ddolib.examples.max2sat.NaiveMax2SatSolver
best() - Method in class org.ddolib.examples.mcp.NaiveMCPSolver
bestInFrontier() - Method in interface org.ddolib.ddo.core.frontier.Frontier: Returns the current best upper bound among all subproblems stored in the frontier.
bestInFrontier() - Method in class org.ddolib.ddo.core.frontier.SimpleFrontier: Returns the best (lowest) lower bound among the subproblems in the frontier.
bestSolution() - Method in class org.ddolib.acs.core.solver.ACSSolver: Returns the set of decisions corresponding to the best solution found, if any.
bestSolution() - Method in class org.ddolib.astar.core.solver.AStarSolver
bestSolution() - Method in class org.ddolib.awastar.core.solver.AwAstarSolver
bestSolution() - Method in interface org.ddolib.common.solver.Solver: Returns the set of decisions that lead to the best solution found by this solver, if any.
bestSolution() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram: Returns the sequence of decisions leading to the best solution represented in this DD.
bestSolution() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Returns the set of decisions representing the best solution found in this MDD.
bestSolution() - Method in class org.ddolib.ddo.core.solver.ExactSolver: Returns the best solution found so far as a set of decisions.
bestSolution() - Method in class org.ddolib.ddo.core.solver.RelaxationSolver
bestSolution() - Method in class org.ddolib.ddo.core.solver.RestrictionSolver
bestSolution() - Method in class org.ddolib.ddo.core.solver.SequentialSolver
bestSolution() - Method in class org.ddolib.examples.max2sat.NaiveMax2SatSolver
bestSolution() - Method in class org.ddolib.examples.mcp.NaiveMCPSolver
bestSolution() - Method in class org.ddolib.lns.core.solver.LNSSolver
bestUB - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Best known upper bound on the objective value at compilation time.
bestValue() - Method in class org.ddolib.acs.core.solver.ACSSolver: Returns the value of the best solution found, if any.
bestValue() - Method in class org.ddolib.astar.core.solver.AStarSolver
bestValue() - Method in class org.ddolib.awastar.core.solver.AwAstarSolver
bestValue() - Method in interface org.ddolib.common.solver.Solver
bestValue() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram: Returns the value of the best solution represented in this decision diagram, if it exists.
bestValue() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Returns the value of the best solution found in this decision diagram, if any.
bestValue() - Method in class org.ddolib.ddo.core.solver.ExactSolver: Returns the value of the best solution found so far.
bestValue() - Method in class org.ddolib.ddo.core.solver.RelaxationSolver
bestValue() - Method in class org.ddolib.ddo.core.solver.RestrictionSolver
bestValue() - Method in class org.ddolib.ddo.core.solver.SequentialSolver
bestValue() - Method in class org.ddolib.lns.core.solver.LNSSolver
BinaryClause - Class in org.ddolib.examples.max2sat: Class to model a Binary clause of two literals for CNF formula.
BinaryClause(int, int) - Constructor for class org.ddolib.examples.max2sat.BinaryClause
BKSAcsMain - Class in org.ddolib.examples.boundedknapsack: Bounded Knapsack Problem (BKS) with Acs.
BKSAcsMain() - Constructor for class org.ddolib.examples.boundedknapsack.BKSAcsMain
BKSAstarMain - Class in org.ddolib.examples.boundedknapsack: Bounded Knapsack Problem (BKS) with AsTar.
BKSAstarMain() - Constructor for class org.ddolib.examples.boundedknapsack.BKSAstarMain
BKSDdoMain - Class in org.ddolib.examples.boundedknapsack: Bounded Knapsack Problem (BKS) with Ddo.
BKSDdoMain() - Constructor for class org.ddolib.examples.boundedknapsack.BKSDdoMain
BKSDominance - Class in org.ddolib.examples.boundedknapsack: Implementation of a dominance rule for the Bounded Knapsack (BKS) problem.
BKSDominance() - Constructor for class org.ddolib.examples.boundedknapsack.BKSDominance
BKSFastLowerBound - Class in org.ddolib.examples.boundedknapsack: A fast lower bound implementation for the BKSProblem (Bounded Knapsack Problem).
BKSFastLowerBound(BKSProblem) - Constructor for class org.ddolib.examples.boundedknapsack.BKSFastLowerBound: Constructs a fast lower bound evaluator for the given bounded knapsack problem.
BKSLnsMain - Class in org.ddolib.examples.boundedknapsack: Entry point for solving the Bounded Knapsack Problem (BKS) using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
BKSLnsMain() - Constructor for class org.ddolib.examples.boundedknapsack.BKSLnsMain
BKSProblem - Class in org.ddolib.examples.boundedknapsack: Represents an instance of the Bounded Knapsack Problem (BKP).
BKSProblem(int, int[], int[], int[]) - Constructor for class org.ddolib.examples.boundedknapsack.BKSProblem: Constructs a bounded knapsack problem from explicitly given parameters.
BKSProblem(int, int, BKSProblem.InstanceType, long) - Constructor for class org.ddolib.examples.boundedknapsack.BKSProblem: Randomly generates an instance of the bounded knapsack problem.
BKSProblem.InstanceType - Enum Class in org.ddolib.examples.boundedknapsack: Enumeration defining possible correlation types between item weights and profits when generating random instances.
BKSRanking - Class in org.ddolib.examples.boundedknapsack: A default state ranking implementation for the Bounded Knapsack Problem (BKP).
BKSRanking() - Constructor for class org.ddolib.examples.boundedknapsack.BKSRanking
BKSRelax - Class in org.ddolib.examples.boundedknapsack: A relaxation strategy for the Bounded Knapsack Problem (BKP) used in relaxed decision diagrams.
BKSRelax() - Constructor for class org.ddolib.examples.boundedknapsack.BKSRelax: Default constructor.

C

cache - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Optional cache to store previously computed states and avoid redundant work.
Cache<T> - Interface in org.ddolib.ddo.core.cache: Defines the abstraction of a cache mechanism used to prune and reduce the search space during the compilation or exploration of a Decision Diagram (DD).
capa - Variable in class org.ddolib.examples.knapsack.KSProblem: Maximum capacity of the knapsack.
capacity - Variable in class org.ddolib.examples.boundedknapsack.BKSProblem
centralities - Variable in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Relative frequency (centrality) of each item in all subsets.
checkFlbAdmissibility(Set<StateAndDepth<T>>, Model<T>, Function<StateAndDepth<T>, Solver>) - Static method in class org.ddolib.util.debug.DebugUtil: Given a set of states check if the FastLowerBound is admissible, i.e., whether the bound does not overestimate the path from the states to a terminal node.
checkFlbConsistency(SubProblem<T>, SubProblem<T>, double) - Static method in class org.ddolib.util.debug.DebugUtil: Given the current node and one of its successor.
checkHashCodeAndEquality(T, Decision, BiFunction<T, Decision, T>) - Static method in class org.ddolib.util.debug.DebugUtil: Checks the consistency of a transition function by generating two states from the same origin state and decision, then verifying that they are equal and have the same hash code.
classTransitionCost - Variable in class org.ddolib.examples.alp.ALPProblem: Minimum separation times between aircraft classes.
clear() - Method in class org.ddolib.ddo.core.cache.SimpleCache.Layer: Clears all entries in the layer.
clear() - Method in interface org.ddolib.ddo.core.frontier.Frontier: Removes all subproblems currently stored in the frontier.
clear() - Method in class org.ddolib.ddo.core.frontier.SimpleFrontier: Clears all subproblems from the frontier.
clear(int) - Method in interface org.ddolib.ddo.core.cache.Cache: Clears cache data up to a specified depth.
clear(int) - Method in class org.ddolib.ddo.core.cache.SimpleCache: Clears all layers of the cache up to the given number of variables.
clearLayer(int) - Method in interface org.ddolib.ddo.core.cache.Cache: Removes all thresholds associated with states at the specified depth.
clearLayer(int) - Method in class org.ddolib.ddo.core.cache.SimpleCache: Clears all thresholds in a specific layer.
clone() - Method in class org.ddolib.examples.mks.MKSState: Creates a deep copy of this state.
clone() - Method in class org.ddolib.examples.pigmentscheduling.PSState: Creates a deep copy of this state.
columnWidth() - Method in interface org.ddolib.modeling.AcsModel: Returns the default column width used for formatted output during the Anytime Column Search process.
compare(Integer, Integer) - Method in class org.ddolib.examples.boundedknapsack.BKSRanking: Compares two states based on their remaining capacity.
compare(Integer, Integer) - Method in class org.ddolib.examples.knapsack.KSRanking: Compares two states based on their remaining capacity.
compare(BitSet, BitSet) - Method in class org.ddolib.examples.misp.MispRanking: Compares two states based on the number of remaining nodes.
compare(NodeSubProblem<T>, NodeSubProblem<T>) - Method in class org.ddolib.ddo.core.mdd.NodeSubProblemComparator: Compares two NodeSubProblem instances.
compare(ALPState, ALPState) - Method in class org.ddolib.examples.alp.ALPRanking: Compares two ALP states according to the number of remaining aircraft and the sum of runway previous landing times.
compare(GRState, GRState) - Method in class org.ddolib.examples.gruler.GRRanking: Compares two GRState instances based on their last placed mark.
compare(LCSState, LCSState) - Method in class org.ddolib.examples.lcs.LCSRanking: Compares two LCS states.
compare(Max2SatState, Max2SatState) - Method in class org.ddolib.examples.max2sat.Max2SatRanking
compare(MaxCoverState, MaxCoverState) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverRanking: Compares two MaxCover states based on the number of items they cover.
compare(MCPState, MCPState) - Method in class org.ddolib.examples.mcp.MCPRanking
compare(MKSState, MKSState) - Method in class org.ddolib.examples.mks.MKSRanking: Compares two MKS states based on their average remaining capacities.
compare(MSCTState, MSCTState) - Method in class org.ddolib.examples.msct.MSCTRanking: Compares two scheduling states according to their current completion time.
compare(PDPState, PDPState) - Method in class org.ddolib.examples.pdp.PDPRanking: Compares two PDP states to determine their relative rank.
compare(PSState, PSState) - Method in class org.ddolib.examples.pigmentscheduling.PSRanking: Compares two PSP states based on their total remaining demand.
compare(SMICState, SMICState) - Method in class org.ddolib.examples.smic.SMICRanking: Compares two SMICState instances based on their current time.
compare(SRFLPState, SRFLPState) - Method in class org.ddolib.examples.srflp.SRFLPRanking: Compares two SRFLP states based on the total number of remaining departments.
compare(TSState, TSState) - Method in class org.ddolib.examples.talentscheduling.TSRanking: Compares two TSState instances based on the total number of scenes in their remainingScenes and maybeScenes sets.
compare(TSPState, TSPState) - Method in class org.ddolib.examples.tsp.TSPRanking: Compares two TSP states.
compare(TSPTWState, TSPTWState) - Method in class org.ddolib.examples.tsptw.TSPTWRanking: Compares two TSPTWState objects based on the size of their possiblyVisit set.
compareTo(Threshold) - Method in class org.ddolib.ddo.core.cache.Threshold: Compares this threshold to another threshold.
compareTo(RunwayState) - Method in class org.ddolib.examples.alp.RunwayState
compareTo(BinaryClause) - Method in class org.ddolib.examples.max2sat.BinaryClause: Used to compare binary clauses.
CompilationConfig<T> - Class in org.ddolib.ddo.core.compilation: Represents the configuration parameters used during the compilation of a Multi-valued Decision Diagram (MDD) or similar decision structure.
CompilationConfig(Model<T>) - Constructor for class org.ddolib.ddo.core.compilation.CompilationConfig: Constructs a new compilation configuration for the given model.
compilationType - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Specifies how the MDD is compiled.
CompilationType - Enum Class in org.ddolib.ddo.core.compilation: Specifies the type of compilation to use when constructing a decision diagram (DD) for a problem.
compile() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram: Triggers the compilation of the decision diagram according to the configuration parameters provided by the user (e.g., width, relaxation, variable heuristic, etc.).
compile() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Compiles the decision diagram according to the configuration: Exact, relaxed, or restricted compilation type. Layer-wise variable ordering and heuristics. Application of relaxations or restrictions based on width limits. Construction of the DOT graph if export or debugging is enabled. Optional caching of thresholds for faster branch-and-bound computations.
constructSolution(Set<Decision>) - Method in interface org.ddolib.common.solver.Solver: Constructs an array representing the values assigned to each variable from a set of decisions.
containsKey(T) - Method in class org.ddolib.ddo.core.cache.SimpleCache.Layer: Checks whether the layer contains a given state, updating hit/test statistics.
Contract: - Search tag in interface org.ddolib.ddo.core.frontier.Frontier: Section
copy() - Method in class org.ddolib.ddo.core.compilation.CompilationConfig: Creates a shallow copy of this configuration.
copy() - Method in class org.ddolib.examples.gruler.GRState: Creates and returns a deep copy of this state.
CostBased<T> - Class in org.ddolib.ddo.core.heuristics.cluster: This strategy select the nodes based on the objective value of the best path leading to them.
CostBased(StateRanking<T>) - Constructor for class org.ddolib.ddo.core.heuristics.cluster.CostBased
coveredItems() - Method in record class org.ddolib.examples.maximumcoverage.MaxCoverState: Returns the value of the coveredItems record component.
currentSubProblem(int, SubProblem<T>) - Method in class org.ddolib.util.verbosity.VerboseMode: Prints message describing the current explored sub problem.
currentTime() - Method in record class org.ddolib.examples.msct.MSCTState: Returns the value of the currentTime record component.
currentTime() - Method in record class org.ddolib.examples.smic.SMICState: Returns the value of the currentTime record component.
cut() - Method in record class org.ddolib.examples.srflp.SRFLPState: Returns the value of the cut record component.
cutSetType - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Defines the cut set strategy used to control node expansion and pruning.
cutSetType() - Method in interface org.ddolib.ddo.core.frontier.Frontier: Returns the type of cut set associated with this frontier.
cutSetType() - Method in class org.ddolib.ddo.core.frontier.SimpleFrontier: Returns the type of cutset used in the frontier.
CutSetType - Enum Class in org.ddolib.ddo.core.frontier: Cutset type for the decision diagram compilation.

D

Data file format - Search tag in class org.ddolib.examples.tsptw.TSPTWProblem: Section
DdoModel<T> - Interface in org.ddolib.modeling: Defines the interface for a Dynamic Decision Diagram Optimization (DDO) model.
debugLevel - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Debugging level controlling logging and internal consistency checks.
DebugLevel - Enum Class in org.ddolib.util.debug: Defines the different levels of debugging information and validation that can be enabled during the execution of the solver.
debugMode() - Method in interface org.ddolib.modeling.Model: Returns the debugging level to apply during the compilation and solving phases.
DebugUtil - Class in org.ddolib.util.debug: Utility class providing methods useful for debugging state transitions.
DebugUtil() - Constructor for class org.ddolib.util.debug.DebugUtil
decision - Variable in class org.ddolib.ddo.core.mdd.Edge: The decision associated with this edge.
Decision - Record Class in org.ddolib.ddo.core: Represents a single decision within an optimization problem.
Decision(int, int) - Constructor for record class org.ddolib.ddo.core.Decision: Creates an instance of a Decision record class.
DecisionDiagram<T> - Interface in org.ddolib.ddo.core.mdd: Defines the abstraction of a reusable Decision Diagram (DD) used to model and solve combinatorial optimization problems.
DefaultDominanceChecker<T> - Class in org.ddolib.common.dominance: Default implementation of a DominanceChecker that performs no dominance checking.
DefaultDominanceChecker() - Constructor for class org.ddolib.common.dominance.DefaultDominanceChecker: Constructs a default dominance checker that never declares any state as dominated.
DefaultFastLowerBound<T> - Class in org.ddolib.modeling: Default implementation of the FastLowerBound interface that always returns Integer.MIN_VALUE as the lower bound estimate.
DefaultFastLowerBound() - Constructor for class org.ddolib.modeling.DefaultFastLowerBound
DefaultVariableHeuristic<T> - Class in org.ddolib.ddo.core.heuristics.variable: A default implementation of VariableHeuristic that selects the next variable to branch on without applying any specific strategy.
DefaultVariableHeuristic() - Constructor for class org.ddolib.ddo.core.heuristics.variable.DefaultVariableHeuristic
defineClusters(List<NodeSubProblem<T>>, int) - Method in class org.ddolib.ddo.core.heuristics.cluster.CostBased: Select the layer.size() - maxWidth - 1 nodes with the worst cost on the layer.
defineClusters(List<NodeSubProblem<T>>, int) - Method in class org.ddolib.ddo.core.heuristics.cluster.GHP: Partitions the given layer into clusters using Generalized Hyperplane Partitioning.
defineClusters(List<NodeSubProblem<T>>, int) - Method in class org.ddolib.ddo.core.heuristics.cluster.Hybrid: Defines clusters from a layer of nodes using a hybrid strategy.
defineClusters(List<NodeSubProblem<T>>, int) - Method in class org.ddolib.ddo.core.heuristics.cluster.RandomBased: Defines clusters by randomly selecting up to maxWidth nodes from the layer.
defineClusters(List<NodeSubProblem<T>>, int) - Method in interface org.ddolib.ddo.core.heuristics.cluster.ReductionStrategy: Generates clusters of nodes for restriction and relaxation from the given layer.
depth() - Method in record class org.ddolib.examples.max2sat.Max2SatState: Returns the value of the depth record component.
depth() - Method in record class org.ddolib.examples.mcp.MCPState: Returns the value of the depth record component.
depth() - Method in record class org.ddolib.examples.srflp.SRFLPState: Returns the value of the depth record component.
depth() - Method in record class org.ddolib.examples.tsptw.TSPTWState: Returns the value of the depth record component.
depth() - Method in record class org.ddolib.util.StateAndDepth: Returns the value of the depth record component.
detailedSearchState(int, int, double, double, double) - Method in class org.ddolib.util.verbosity.VerboseMode: Prints statistics about the frontier after every half second.
diceDistance(BitSet, BitSet) - Static method in class org.ddolib.util.DistanceUtil: Computes the Dice Distance between the two given sets.
disableDominance() - Method in interface org.ddolib.modeling.AcsModel
disableDominance() - Method in interface org.ddolib.modeling.DdoModel
disableDominance() - Method in interface org.ddolib.modeling.Model: Returns a copy of this model but without dominance.
disableLowerBound() - Method in interface org.ddolib.modeling.AcsModel
disableLowerBound() - Method in interface org.ddolib.modeling.DdoModel
disableLowerBound() - Method in interface org.ddolib.modeling.Model: Returns a copy of this model but without FastLowerBound.
dist(double, double, double, double) - Method in class org.ddolib.examples.tsp.TSPGenerator: Computes the Euclidean distance between two points.
dist(int, int) - Static method in class org.ddolib.examples.pdp.PDPGenerator: Computes the Euclidean distance between two points.
distance - Variable in class org.ddolib.examples.tsptw.TSPTWProblem: Distance matrix between nodes.
distance(int, int) - Method in class org.ddolib.examples.tsp.TSPGenerator: Returns the distance between two cities.
distance(Integer, Integer) - Method in class org.ddolib.examples.knapsack.KSDistance: Computes the normalized distance between two states.
distance(NodeSubProblem<MaxCoverState>, NodeSubProblem<MaxCoverState>) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverDistance: Computes the distance between two search nodes.
distance(NodeSubProblem<T>, NodeSubProblem<T>) - Method in interface org.ddolib.ddo.core.heuristics.cluster.StateDistance: Computes the distance between two nodes of a subproblem.
distance(MaxCoverState, MaxCoverState) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverDistance: Computes the distance between two MaxCover states.
distance(MKSState, MKSState) - Method in class org.ddolib.examples.mks.MKSDistance: Computes the normalized Euclidean distance between two MKS states.
distance(TSState, TSState) - Method in class org.ddolib.examples.talentscheduling.TSDistance
distance(T, T) - Method in interface org.ddolib.ddo.core.heuristics.cluster.StateDistance: Computes the discrete distance between two states.
distanceMatrix - Variable in class org.ddolib.examples.pdp.PDPProblem: Distance matrix between all nodes.
distanceMatrix - Variable in class org.ddolib.examples.tsp.TSPGenerator: Distance matrix between cities
distanceMatrix - Variable in class org.ddolib.examples.tsp.TSPProblem: Distance matrix between nodes
DistanceUtil - Class in org.ddolib.util
DistanceUtil() - Constructor for class org.ddolib.util.DistanceUtil
distanceWithRoot(Integer) - Method in class org.ddolib.examples.knapsack.KSDistance: Computes the normalized distance between a state and the root (empty knapsack).
distanceWithRoot(MaxCoverState) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverDistance: Computes the distance between a state and the root of the search tree.
distanceWithRoot(MKSState) - Method in class org.ddolib.examples.mks.MKSDistance: Computes the normalized Euclidean distance from the given state to the initial state.
distanceWithRoot(T) - Method in interface org.ddolib.ddo.core.heuristics.cluster.StateDistance: Computes the distance between a state and the root of the search/tree.
domain(Integer, int) - Method in class org.ddolib.examples.boundedknapsack.BKSProblem: Returns the domain (set of possible values) for a given variable (item), given the current remaining capacity.
domain(Integer, int) - Method in class org.ddolib.examples.knapsack.KSProblem
domain(BitSet, int) - Method in class org.ddolib.examples.misp.MispProblem
domain(ALPState, int) - Method in class org.ddolib.examples.alp.ALPProblem
domain(GRState, int) - Method in class org.ddolib.examples.gruler.GRProblem: Returns the possible domain values for the next decision (i.e., possible positions for the next mark).
domain(LCSState, int) - Method in class org.ddolib.examples.lcs.LCSProblem: Computes the domain of possible next decisions (characters) for a given state.
domain(Max2SatState, int) - Method in class org.ddolib.examples.max2sat.Max2SatProblem
domain(MaxCoverState, int) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns an iterator over the domain of values for a given variable in a state.
domain(MCPState, int) - Method in class org.ddolib.examples.mcp.MCPProblem
domain(MKSState, int) - Method in class org.ddolib.examples.mks.MKSProblem: Returns an iterator over the domain of a variable (item) in a given state.
domain(MSCTState, int) - Method in class org.ddolib.examples.msct.MSCTProblem: Returns the domain of possible decisions at the current state.
domain(PDPState, int) - Method in class org.ddolib.examples.pdp.PDPProblem: Returns the domain of possible decisions (nodes to visit) from a given state and variable index.
domain(PSState, int) - Method in class org.ddolib.examples.pigmentscheduling.PSProblem: Defines the domain of feasible decisions (items to produce or idle) for a given state and time depth.
domain(SMICState, int) - Method in class org.ddolib.examples.smic.SMICProblem: Returns the feasible domain of jobs that can be scheduled next, given the current inventory and remaining capacity constraints.
domain(SRFLPState, int) - Method in class org.ddolib.examples.srflp.SRFLPProblem
domain(TSState, int) - Method in class org.ddolib.examples.talentscheduling.TSProblem
domain(TSPState, int) - Method in class org.ddolib.examples.tsp.TSPProblem: Returns the domain of possible decisions for a given state and variable index.
domain(TSPTWState, int) - Method in class org.ddolib.examples.tsptw.TSPTWProblem
domain(T, int) - Method in interface org.ddolib.modeling.Problem: Returns the domain of possible values for a given variable when applied to a specific state.
dominance - Variable in class org.ddolib.common.dominance.DominanceChecker
dominance - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Dominance checker used to prune dominated states and reduce the size of the search space.
dominance() - Method in interface org.ddolib.modeling.Model: Returns the dominance checker used to prune dominated states from the search space.
Dominance<T> - Interface in org.ddolib.modeling: Defines a dominance relation used to compare and prune states during the exploration of decision diagrams or search spaces.
DominanceChecker<T> - Class in org.ddolib.common.dominance: Object that, given a dominance, will check if a state is dominated.
DominanceChecker(Dominance<T>) - Constructor for class org.ddolib.common.dominance.DominanceChecker
DominanceKey<T,K> - Interface in org.ddolib.modeling: Defines a function that extracts a canonical dominance key from a given state.
DUMMY - Static variable in class org.ddolib.examples.alp.ALPProblem

E

Edge - Class in org.ddolib.ddo.core.mdd: Represents an edge in a decision diagram that connects two nodes.
Edge(Node, Decision, double) - Constructor for class org.ddolib.ddo.core.mdd.Edge: Creates a new edge connecting a source node with a decision and a weight.
edges - Variable in class org.ddolib.ddo.core.mdd.Node: The list of edges leading to this node.
end() - Method in record class org.ddolib.examples.tsptw.TimeWindow: Returns the value of the end record component.
equals(Object) - Method in record class org.ddolib.common.solver.SearchStatistics: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.ddo.core.Decision: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class org.ddolib.ddo.core.SubProblem: Compares this subproblem to another for equality.
equals(Object) - Method in class org.ddolib.examples.alp.ALPDecision: Checks whether this decision is equal to another object.
equals(Object) - Method in class org.ddolib.examples.alp.ALPState: Checks if two ALP states are equal.
equals(Object) - Method in class org.ddolib.examples.alp.RunwayState
equals(Object) - Method in class org.ddolib.examples.gruler.GRState: Compares this state to another for equality.
equals(Object) - Method in class org.ddolib.examples.lcs.LCSRanking: Indicates whether this ranking object is equal to another.
equals(Object) - Method in class org.ddolib.examples.lcs.LCSState: Checks equality between this state and another object.
equals(Object) - Method in class org.ddolib.examples.max2sat.BinaryClause
equals(Object) - Method in record class org.ddolib.examples.max2sat.Max2SatState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.examples.maximumcoverage.MaxCoverState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.examples.mcp.MCPState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class org.ddolib.examples.mks.MKSState: Compares this state to another object for equality.
equals(Object) - Method in record class org.ddolib.examples.msct.MSCTState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class org.ddolib.examples.pdp.PDPState
equals(Object) - Method in class org.ddolib.examples.pigmentscheduling.PSState: Compares this state with another object for equality.
equals(Object) - Method in record class org.ddolib.examples.smic.SMICState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.examples.srflp.SRFLPState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.examples.talentscheduling.TSState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class org.ddolib.examples.tsp.TSPState
equals(Object) - Method in record class org.ddolib.examples.tsptw.TimeWindow: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.examples.tsptw.TSPTWDominanceKey: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.examples.tsptw.TSPTWState: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class org.ddolib.util.StateAndDepth: Indicates whether some other object is "equal to" this one.
euclideanDistance(double[], double[]) - Static method in class org.ddolib.util.DistanceUtil: Computes the Euclidean Distance between the two given arrays of coordinates
eval(int[]) - Method in class org.ddolib.examples.pdp.PDPProblem: Evaluates a solution represented as an array of node indices.
eval(int[]) - Method in class org.ddolib.examples.tsp.TSPProblem: Evaluates the total tour cost for a given solution.
eval(int, int) - Method in class org.ddolib.examples.max2sat.BinaryClause: Evaluates if the clause is verified given 2 boolean values.
evaluate(int[]) - Method in class org.ddolib.examples.alp.ALPProblem
evaluate(int[]) - Method in class org.ddolib.examples.boundedknapsack.BKSProblem
evaluate(int[]) - Method in class org.ddolib.examples.gruler.GRProblem
evaluate(int[]) - Method in class org.ddolib.examples.knapsack.KSProblem
evaluate(int[]) - Method in class org.ddolib.examples.lcs.LCSProblem
evaluate(int[]) - Method in class org.ddolib.examples.max2sat.Max2SatProblem
evaluate(int[]) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Evaluates a complete solution.
evaluate(int[]) - Method in class org.ddolib.examples.mcp.MCPProblem
evaluate(int[]) - Method in class org.ddolib.examples.misp.MispProblem
evaluate(int[]) - Method in class org.ddolib.examples.mks.MKSProblem: Evaluates the cost of a given solution.
evaluate(int[]) - Method in class org.ddolib.examples.msct.MSCTProblem
evaluate(int[]) - Method in class org.ddolib.examples.pdp.PDPProblem
evaluate(int[]) - Method in class org.ddolib.examples.pigmentscheduling.PSProblem
evaluate(int[]) - Method in class org.ddolib.examples.smic.SMICProblem
evaluate(int[]) - Method in class org.ddolib.examples.srflp.SRFLPProblem
evaluate(int[]) - Method in class org.ddolib.examples.talentscheduling.TSProblem
evaluate(int[]) - Method in class org.ddolib.examples.tsp.TSPProblem
evaluate(int[]) - Method in class org.ddolib.examples.tsptw.TSPTWProblem
evaluate(int[]) - Method in interface org.ddolib.modeling.Problem: Given a solution such that solution[i] is the value of the variable x_i, returns the value of this solution and checks if the solution respects the problem's constraints.
Exact - Enum constant in enum class org.ddolib.ddo.core.compilation.CompilationType: Compile an exact decision diagram.
EXACT - Enum constant in enum class org.ddolib.ddo.core.mdd.NodeType: Represents an exact node in the decision diagram.
exactCutset() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram: Provides an iterator over the nodes belonging to the exact cutset of the diagram.
exactCutset() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Returns an iterator over the nodes in the exact cutset, transformed into subproblems.
ExactModel<T> - Class in org.ddolib.modeling: Defines the interface for a Dynamic Decision Diagram Optimization (DDO) model, used by the ExactSolver
ExactModel() - Constructor for class org.ddolib.modeling.ExactModel
ExactSolver<T> - Class in org.ddolib.ddo.core.solver: Solver that compiles a single exact decision diagram (MDD) to find the optimal solution.
ExactSolver(ExactModel<T>) - Constructor for class org.ddolib.ddo.core.solver.ExactSolver: Creates a fully-configured ExactSolver instance.
Example - Search tag in class org.ddolib.examples.smic.SMICGenrator: Section
Example Usage - Search tag in record class org.ddolib.examples.smic.SMICState: Section
Execution - Search tag in class org.ddolib.examples.alp.ALPLnsMain: Section
Execution - Search tag in class org.ddolib.examples.knapsack.KSLnsMain: Section
Execution - Search tag in class org.ddolib.examples.lcs.LCSLnsMain: Section
Execution - Search tag in class org.ddolib.examples.max2sat.Max2SatLnsMain: Section
Execution - Search tag in class org.ddolib.examples.mcp.MCPLnsMain: Section
Execution - Search tag in class org.ddolib.examples.misp.MispLnsMain: Section
Execution - Search tag in class org.ddolib.examples.msct.MSCTLnsMain: Section
EXPORT - Enum constant in enum class org.ddolib.util.verbosity.VerbosityLevel: Same that LARGE but save the logs into logs.txt files.
exportAsDot - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Indicates whether the compiled MDD should be exported as a DOT file (Graphviz format) for visualization purposes.
exportAsDot() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram: Exports the compiled decision diagram as a Graphviz-compatible DOT formatted string.
exportAsDot() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Exports the compiled decision diagram in DOT format.
exportDot() - Method in interface org.ddolib.modeling.DdoModel: Indicates whether the generated decision diagram should be exported to a DOT file (Graphviz format).
exportDot() - Method in interface org.ddolib.modeling.LnsModel: Indicates whether to export the search tree to DOT format.
EXTENDED - Enum constant in enum class org.ddolib.util.debug.DebugLevel: Enables extended debugging and diagnostic tools.

F

f() - Method in class org.ddolib.ddo.core.SubProblem: Computes and returns the f-value of this subproblem, defined as the sum of its current objective value and its lower bound.
f(int) - Method in class org.ddolib.examples.max2sat.Max2SatProblem: Returns the negated literal for a variable.
fastLowerBound(Integer, Set<Integer>) - Method in class org.ddolib.examples.boundedknapsack.BKSFastLowerBound: Computes a fast lower bound for the given state and remaining variables.
fastLowerBound(Integer, Set<Integer>) - Method in class org.ddolib.examples.knapsack.KSFastLowerBound: Computes a fast lower bound for the given knapsack state.
fastLowerBound(BitSet, Set<Integer>) - Method in class org.ddolib.examples.misp.MispFastLowerBound: Computes a fast lower bound for the given state and set of remaining variables.
fastLowerBound(ALPState, Set<Integer>) - Method in class org.ddolib.examples.alp.ALPFastLowerBound: Computes a heuristic lower bound of total tardiness from the given state.
fastLowerBound(GRState, Set<Integer>) - Method in class org.ddolib.examples.gruler.GRFastLowerBound
fastLowerBound(LCSState, Set<Integer>) - Method in class org.ddolib.examples.lcs.LCSFastLowerBound: Computes a fast lower bound on the objective function for the given state.
fastLowerBound(Max2SatState, Set<Integer>) - Method in class org.ddolib.examples.max2sat.Max2SatFastLowerBound: Computes the fast lower bound for a given state and set of remaining variables.
fastLowerBound(MaxCoverState, Set<Integer>) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverFastLowerBound: Computes a fast lower bound on the objective value from a given state.
fastLowerBound(MCPState, Set<Integer>) - Method in class org.ddolib.examples.mcp.MCPFastLowerBound
fastLowerBound(MKSState, Set<Integer>) - Method in class org.ddolib.examples.mks.MKSFastLowerBound: Computes a fast lower bound for a given state and a set of variables (items).
fastLowerBound(MSCTState, Set<Integer>) - Method in class org.ddolib.examples.msct.MSCTFastLowerBound: Computes a fast lower bound on the total completion time (or cost) from the given state and remaining variables.
fastLowerBound(PDPState, Set<Integer>) - Method in class org.ddolib.examples.pdp.PDPFastLowerBound: Computes a fast lower bound for a given state and a set of unassigned variables.
fastLowerBound(PSState, Set<Integer>) - Method in class org.ddolib.examples.pigmentscheduling.PSFastLowerBound: Computes a fast (but admissible) lower bound on the remaining production cost for the given PSP state.
fastLowerBound(SMICState, Set<Integer>) - Method in class org.ddolib.examples.smic.SMICFastLowerBound: Computes a fast lower bound for the current search state.
fastLowerBound(SRFLPState, Set<Integer>) - Method in class org.ddolib.examples.srflp.SRFLPFastLowerBound: Computes a fast lower bound for a given state and a set of variables.
fastLowerBound(TSState, Set<Integer>) - Method in class org.ddolib.examples.talentscheduling.TSFastLowerBound: Computes a fast lower bound on the total cost from the given partial state.
fastLowerBound(TSPState, Set<Integer>) - Method in class org.ddolib.examples.tsp.TSPFastLowerBound: Computes a fast lower bound on the cost to complete the TSP tour from the given state.
fastLowerBound(TSPTWState, Set<Integer>) - Method in class org.ddolib.examples.tsptw.TSPTWFastLowerBound: Computes a fast lower bound on the remaining tour cost from the given state.
fastLowerBound(T, Set<Integer>) - Method in class org.ddolib.modeling.DefaultFastLowerBound: Computes a trivial fast lower bound for the given state and remaining variables.
fastLowerBound(T, Set<Integer>) - Method in interface org.ddolib.modeling.FastLowerBound: Returns a very rough estimation (upper bound) of the optimal value that could be reached if state were the initial state.
FastLowerBound<T> - Interface in org.ddolib.modeling: Interface for the fast lower bound method Heuristic defining a fast lower bound for states
FixedWidth<T> - Class in org.ddolib.ddo.core.heuristics.width: Implements a static maximum width heuristic for decision diagram or search-based algorithms.
FixedWidth(int) - Constructor for class org.ddolib.ddo.core.heuristics.width.FixedWidth: Constructs a new FixedWidth heuristic with the specified maximum width.
fixWidth(int) - Method in interface org.ddolib.modeling.DdoModel: Returns a copy of this model but with a fixed width.
fixWidth(int) - Method in interface org.ddolib.modeling.LnsModel: Returns a copy of this model with a fixed search width.
flb - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Fast lower bound heuristic used to estimate the best achievable objective value from a given state.
flb - Variable in class org.ddolib.ddo.core.mdd.Node: Overapproximation of the shortest path from this node to a terminal node.
flb - Variable in class org.ddolib.ddo.core.mdd.NodeSubProblem: The fast lower bound of this node (this node to terminal node)
formatMs(long) - Static method in class org.ddolib.util.PrettyPrint: Formats a duration in milliseconds into a human-readable string.
fromDecision(int) - Method in class org.ddolib.examples.alp.ALPProblem: Restores an ALPDecision from its integer representation.
frontier() - Method in interface org.ddolib.modeling.DdoModel: Returns the frontier management strategy used to store and expand the current layer of the decision diagram.
frontier() - Method in class org.ddolib.modeling.ExactModel
Frontier - Enum constant in enum class org.ddolib.ddo.core.frontier.CutSetType: The cut set is defined by the current search frontier — the set of nodes that are candidates for expansion.
Frontier<T> - Interface in org.ddolib.ddo.core.frontier: Defines the abstraction of a frontier (or open list) used by solvers to manage and prioritize the remaining subproblems that must be explored.

G

gap() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns the value of the gap record component.
generate() - Method in class org.ddolib.examples.smic.SMICGenrator: Generates a random feasible SMICProblem instance based on the parameters provided at construction.
generateCombinations(int, int) - Static method in class org.ddolib.examples.maximumcoverage.MaxCoverGenerator: Generates all non-ordered combinations of k elements from n.
generateRandom(int, String, int) - Static method in class org.ddolib.examples.misp.MispGenerator: Generates a random instance of the MISP.
generateRandom(int, String, int, long) - Static method in class org.ddolib.examples.misp.MispGenerator: Generates a random instance of the MISP.
generateRandomInstance(String, int, int) - Static method in class org.ddolib.examples.max2sat.Max2SatGenerator: Generates and writes a random instance of the Max2Sat.
generateRandomInstance(String, int, int, int, int, long) - Static method in class org.ddolib.examples.lcs.LCSGenerator: Generates and saves a random instance of the LCS
generateRandomInstance(String, int, int, long) - Static method in class org.ddolib.examples.max2sat.Max2SatGenerator: Generates and writes a random instance of the Max2Sat.
Generation Process - Search tag in class org.ddolib.examples.smic.SMICGenrator: Section
genInstance(int, int, int, Random) - Static method in class org.ddolib.examples.pdp.PDPGenerator: Generates a random PDP instance with the given parameters.
get(T) - Method in class org.ddolib.ddo.core.cache.SimpleCache.Layer: Retrieves the threshold for a given state in a thread-safe manner.
getArrivalTime(RunwayState[], int, int) - Method in class org.ddolib.examples.alp.ALPProblem: Computes the arrival time of an aircraft on a given runway.
getDepth() - Method in class org.ddolib.ddo.core.SubProblem: Returns the depth of this subproblem, corresponding to the number of decisions taken from the root to reach it.
getDistances() - Method in class org.ddolib.examples.gruler.GRState: Returns the set of pairwise distances already covered.
getDouble() - Method in class org.ddolib.util.io.InputReader: Reads the next double from the input.
getDoubleMatrix(int, int) - Method in class org.ddolib.util.io.InputReader: Reads a matrix of doubles with the given dimensions.
getExplored() - Method in class org.ddolib.ddo.core.cache.Threshold: Returns whether the state has been explored.
getInt() - Method in class org.ddolib.util.io.InputReader: Reads the next integer from the input.
getIntLine() - Method in class org.ddolib.util.io.InputReader: Reads a full line of integers.
getIntMatrix(int, int) - Method in class org.ddolib.util.io.InputReader: Reads a matrix of integers with the given dimensions.
getKey(Integer) - Method in class org.ddolib.examples.boundedknapsack.BKSDominance: Returns the dominance key for a given state.
getKey(Integer) - Method in class org.ddolib.examples.knapsack.KSDominance: Returns the key used for grouping states in the dominance checker.
getKey(BitSet) - Method in class org.ddolib.examples.misp.MispDominance: Returns a key for the dominance relation.
getKey(MaxCoverState) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverDominance: Returns the dominance key associated with a state.
getKey(MKSState) - Method in class org.ddolib.examples.mks.MKSDominance: Returns a key for grouping states in dominance checks.
getKey(MSCTState) - Method in class org.ddolib.examples.msct.MSCTDominance: Returns a key used for grouping states before applying dominance checks.
getKey(SMICState) - Method in class org.ddolib.examples.smic.SMICDominance: Returns a key used to group comparable states.
getKey(TSPTWState) - Method in class org.ddolib.examples.tsptw.TSPTWDominance: Returns the dominance key for a given state, based on its current position and the set of locations that still must be visited.
getKey(T) - Method in interface org.ddolib.modeling.Dominance: Returns a canonical key associated with a given state.
getLastMark() - Method in class org.ddolib.examples.gruler.GRState: Returns the position of the last placed mark.
getLayer(int) - Method in interface org.ddolib.ddo.core.cache.Cache: Retrieves the cache layer associated with the specified depth.
getLayer(int) - Method in class org.ddolib.ddo.core.cache.SimpleCache: Returns the layer at a given depth.
getLb() - Method in class org.ddolib.ddo.core.mdd.NodeSubProblem
getLowerBound() - Method in class org.ddolib.ddo.core.SubProblem: Returns the lower bound on the global objective that can be achieved by solving the remainder of the problem through this subproblem.
getMarks() - Method in class org.ddolib.examples.gruler.GRState: Returns the set of marks already placed.
getNumberOfMarks() - Method in class org.ddolib.examples.gruler.GRState: Returns the number of marks currently placed.
getOptimalSolution(int[][]) - Static method in class org.ddolib.examples.mcp.NaiveMCPSolver: Given an adjacency matrix, solves naively the instance of MCP.
getPath() - Method in class org.ddolib.ddo.core.SubProblem: Returns the path (partial assignment) of decisions that led to this subproblem.
getState() - Method in class org.ddolib.ddo.core.SubProblem: Returns the root state associated with this subproblem.
getString() - Method in class org.ddolib.util.io.InputReader: Reads the next token as a string.
getThreshold(T, int) - Method in interface org.ddolib.ddo.core.cache.Cache: Retrieves the threshold currently associated with a given state and depth.
getThreshold(T, int) - Method in class org.ddolib.ddo.core.cache.SimpleCache: Retrieves the threshold associated with a given state at a specific depth.
getValue() - Method in class org.ddolib.ddo.core.cache.Threshold: Returns the numeric value of this threshold.
getValue() - Method in class org.ddolib.ddo.core.mdd.NodeSubProblem
getValue() - Method in class org.ddolib.ddo.core.SubProblem: Returns the cumulative objective value at the root of this subproblem.
getWriter() - Method in class org.ddolib.util.verbosity.VerboseMode: Returns a writer depending on the verbosity level.
GHP<T> - Class in org.ddolib.ddo.core.heuristics.cluster: Generalized Hyperplane Partitioning (GHP) reduction strategy for decision diagram layers.
GHP(StateDistance<T>) - Constructor for class org.ddolib.ddo.core.heuristics.cluster.GHP: Constructs a GHP reduction strategy with a default random seed.
GHP(StateDistance<T>, long) - Constructor for class org.ddolib.ddo.core.heuristics.cluster.GHP: Constructs a GHP reduction strategy with a specified random seed.
GRAcsMain - Class in org.ddolib.examples.gruler: Golomb Rule Problem (GRP) with Acs.
GRAcsMain() - Constructor for class org.ddolib.examples.gruler.GRAcsMain
Graph - Class in org.ddolib.examples.mcp: Represents a Graph with adjacency matrix.
Graph(int[][]) - Constructor for class org.ddolib.examples.mcp.Graph: Given an adjacency matrix instantiate a graph.
GRAstarMain - Class in org.ddolib.examples.gruler: Golomb Rule Problem (GRP) with AsTar.
GRAstarMain() - Constructor for class org.ddolib.examples.gruler.GRAstarMain
GRDdoMain - Class in org.ddolib.examples.gruler: Golomb Rule Problem (GRP) with Ddo.
GRDdoMain() - Constructor for class org.ddolib.examples.gruler.GRDdoMain
greedyKS(KSProblem) - Static method in class org.ddolib.examples.knapsack.KSAlgo: Provides a greedy approximation for the Knapsack Problem.
GRFastLowerBound - Class in org.ddolib.examples.gruler: Lower bound for the Golomb Ruler.
GRFastLowerBound() - Constructor for class org.ddolib.examples.gruler.GRFastLowerBound
GRProblem - Class in org.ddolib.examples.gruler: Represents an instance of the Golomb Ruler (GR) problem.
GRProblem(int) - Constructor for class org.ddolib.examples.gruler.GRProblem: Constructs a Golomb Ruler problem with n marks and no known optimal value.
GRProblem(int, double) - Constructor for class org.ddolib.examples.gruler.GRProblem: Constructs a Golomb Ruler problem with n marks and a known optimal length.
GRRanking - Class in org.ddolib.examples.gruler: Defines a ranking strategy for states in the Golomb Ruler (GR) problem.
GRRanking() - Constructor for class org.ddolib.examples.gruler.GRRanking
GRRelax - Class in org.ddolib.examples.gruler: Relaxation operator for the Golomb Ruler (GR) problem.
GRRelax() - Constructor for class org.ddolib.examples.gruler.GRRelax
GRState - Class in org.ddolib.examples.gruler: Represents a state in the Golomb Ruler (GR) problem.
GRState(BitSet, BitSet, int) - Constructor for class org.ddolib.examples.gruler.GRState: Constructs a new GRState from given sets of marks and distances.

H

hashCode() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.ddo.core.Decision: Returns a hash code value for this object.
hashCode() - Method in class org.ddolib.ddo.core.mdd.Node
hashCode() - Method in class org.ddolib.ddo.core.SubProblem: Returns the hash code of this subproblem, derived from its root state.
hashCode() - Method in class org.ddolib.examples.alp.ALPDecision: Computes the hash code of this decision based on the aircraft class and runway.
hashCode() - Method in class org.ddolib.examples.alp.ALPState: Computes the hash code for this state, based on remaining aircraft and runway states.
hashCode() - Method in class org.ddolib.examples.alp.RunwayState
hashCode() - Method in class org.ddolib.examples.gruler.GRState: Computes the hash code for this state based on marks, distances, and the last mark.
hashCode() - Method in class org.ddolib.examples.lcs.LCSState: Returns a hash code for this state, based on the positions in all strings.
hashCode() - Method in class org.ddolib.examples.max2sat.BinaryClause
hashCode() - Method in record class org.ddolib.examples.max2sat.Max2SatState: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.examples.maximumcoverage.MaxCoverState: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.examples.mcp.MCPState: Returns a hash code value for this object.
hashCode() - Method in class org.ddolib.examples.mks.MKSState: Computes the hash code based on the capacities array.
hashCode() - Method in record class org.ddolib.examples.msct.MSCTState: Returns a hash code value for this object.
hashCode() - Method in class org.ddolib.examples.pdp.PDPState
hashCode() - Method in class org.ddolib.examples.pigmentscheduling.PSState: Computes a hash code for the state, based on time, next item, and previous demands.
hashCode() - Method in record class org.ddolib.examples.smic.SMICState: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.examples.srflp.SRFLPState: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.examples.talentscheduling.TSState: Returns a hash code value for this object.
hashCode() - Method in class org.ddolib.examples.tsp.TSPState
hashCode() - Method in record class org.ddolib.examples.tsptw.TimeWindow: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.examples.tsptw.TSPTWDominanceKey: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.examples.tsptw.TSPTWState: Returns a hash code value for this object.
hashCode() - Method in record class org.ddolib.util.StateAndDepth: Returns a hash code value for this object.
Hybrid<T> - Class in org.ddolib.ddo.core.heuristics.cluster: Hybrid reduction strategy that combines cost-based and distance-based clustering for decision diagram layers.
Hybrid(StateRanking<T>, StateDistance<T>) - Constructor for class org.ddolib.ddo.core.heuristics.cluster.Hybrid: Constructs a Hybrid reduction strategy with default alpha (0.5) and seed.
Hybrid(StateRanking<T>, StateDistance<T>, double, long) - Constructor for class org.ddolib.ddo.core.heuristics.cluster.Hybrid: Constructs a Hybrid reduction strategy with specified ranking, distance, alpha, and seed.

I

i - Variable in class org.ddolib.examples.max2sat.BinaryClause
IDLE - Static variable in class org.ddolib.examples.pigmentscheduling.PSProblem: Represents the idle state of the machine (no production).
incumbent() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns the value of the incumbent record component.
initialize(Problem<T>) - Method in interface org.ddolib.ddo.core.cache.Cache: Initializes the cache for use with the specified problem instance.
initialize(Problem<T>) - Method in class org.ddolib.ddo.core.cache.SimpleCache: Initializes the cache based on the number of variables of the problem.
initialSolution - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Initial solution provided to guide the search (e.g., for heuristics or LNS).
initialSolution() - Method in interface org.ddolib.modeling.LnsModel: Returns the initial solution to start the search from.
initialState() - Method in class org.ddolib.examples.alp.ALPProblem
initialState() - Method in class org.ddolib.examples.boundedknapsack.BKSProblem: Returns the initial state of the problem, which corresponds to the remaining capacity of the knapsack before adding any items.
initialState() - Method in class org.ddolib.examples.gruler.GRProblem: Returns the initial state of the problem, containing only the first mark at position 0.
initialState() - Method in class org.ddolib.examples.knapsack.KSProblem
initialState() - Method in class org.ddolib.examples.lcs.LCSProblem
initialState() - Method in class org.ddolib.examples.max2sat.Max2SatProblem
initialState() - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns the initial state for the DDO search.
initialState() - Method in class org.ddolib.examples.mcp.MCPProblem
initialState() - Method in class org.ddolib.examples.misp.MispProblem
initialState() - Method in class org.ddolib.examples.mks.MKSProblem: Returns the initial state for this problem, representing full capacities.
initialState() - Method in class org.ddolib.examples.msct.MSCTProblem: Returns the initial state of the problem, where all jobs are unscheduled.
initialState() - Method in class org.ddolib.examples.pdp.PDPProblem: Returns the initial state of the problem.
initialState() - Method in class org.ddolib.examples.pigmentscheduling.PSProblem: Builds the initial problem state, where no items have been produced and the machine is idle.
initialState() - Method in class org.ddolib.examples.smic.SMICProblem: Returns the initial state of the problem, where all jobs remain to be processed and the machine starts at time 0 with the initial inventory.
initialState() - Method in class org.ddolib.examples.srflp.SRFLPProblem: Computes a constant initial value accounting for half the contribution of each department pair.
initialState() - Method in class org.ddolib.examples.talentscheduling.TSProblem
initialState() - Method in class org.ddolib.examples.tsp.TSPProblem: Returns the initial state for a search algorithm.
initialState() - Method in class org.ddolib.examples.tsptw.TSPTWProblem
initialState() - Method in interface org.ddolib.modeling.Problem: Returns the initial state of the problem.
initialValue() - Method in class org.ddolib.examples.alp.ALPProblem
initialValue() - Method in class org.ddolib.examples.boundedknapsack.BKSProblem: Returns the initial objective value of the problem.
initialValue() - Method in class org.ddolib.examples.gruler.GRProblem: Returns the initial cost (always 0).
initialValue() - Method in class org.ddolib.examples.knapsack.KSProblem
initialValue() - Method in class org.ddolib.examples.lcs.LCSProblem
initialValue() - Method in class org.ddolib.examples.max2sat.Max2SatProblem: Computes the initial value of the problem.
initialValue() - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns the initial objective value for the initial state.
initialValue() - Method in class org.ddolib.examples.mcp.MCPProblem
initialValue() - Method in class org.ddolib.examples.misp.MispProblem
initialValue() - Method in class org.ddolib.examples.mks.MKSProblem: Returns the initial value associated with the initial state.
initialValue() - Method in class org.ddolib.examples.msct.MSCTProblem: Returns the initial cost value of the problem (always 0 at the start).
initialValue() - Method in class org.ddolib.examples.pdp.PDPProblem: Returns the initial value of the problem.
initialValue() - Method in class org.ddolib.examples.pigmentscheduling.PSProblem: Returns the initial objective value associated with the initial state.
initialValue() - Method in class org.ddolib.examples.smic.SMICProblem: Returns the initial objective value associated with the initial state.
initialValue() - Method in class org.ddolib.examples.srflp.SRFLPProblem: Returns a constant accounting for all contributions of half department lengths.
initialValue() - Method in class org.ddolib.examples.talentscheduling.TSProblem
initialValue() - Method in class org.ddolib.examples.tsp.TSPProblem: Returns the initial cost of the problem, which is 0.
initialValue() - Method in class org.ddolib.examples.tsptw.TSPTWProblem
initialValue() - Method in interface org.ddolib.modeling.Problem: Returns the initial objective value associated with the initial state.
InputReader - Class in org.ddolib.util.io: Utility class to read formatted input from a file.
InputReader(String) - Constructor for class org.ddolib.util.io.InputReader: Constructs an InputReader for the specified file.
Instance Configuration - Search tag in class org.ddolib.examples.boundedknapsack.BKSLnsMain: Section
Instance Configuration - Search tag in class org.ddolib.examples.maximumcoverage.MaxCoverLnsMain: Section
Instance Configuration - Search tag in class org.ddolib.examples.pdp.PDPLnsMain: Section
Instance Configuration - Search tag in class org.ddolib.examples.pigmentscheduling.PSLnsMain: Section
instanceFormat() - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns a formatted string representing the instance for writing to a file.
InvalidSolutionException - Exception Class in org.ddolib.modeling: Exception thrown by Problem.evaluate(int[]) method if its input solution does not respect the problem's constraints.
InvalidSolutionException(String) - Constructor for exception class org.ddolib.modeling.InvalidSolutionException
isAboveExactCutSet - Variable in class org.ddolib.ddo.core.mdd.Node: Flag indicating if the node is above the exact cutset.
isDominatedOrEqual(Integer, Integer) - Method in class org.ddolib.examples.boundedknapsack.BKSDominance: Checks whether one state (capacity) is dominated or equal to another.
isDominatedOrEqual(Integer, Integer) - Method in class org.ddolib.examples.knapsack.KSDominance: Checks whether one state is dominated by another.
isDominatedOrEqual(BitSet, BitSet) - Method in class org.ddolib.examples.misp.MispDominance: Determines whether state1 is dominated by or equal to state2.
isDominatedOrEqual(MaxCoverState, MaxCoverState) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverDominance: Determines whether state1 is dominated by or equal to state2.
isDominatedOrEqual(MKSState, MKSState) - Method in class org.ddolib.examples.mks.MKSDominance: Determines whether state1 is dominated by or equal to state2.
isDominatedOrEqual(MSCTState, MSCTState) - Method in class org.ddolib.examples.msct.MSCTDominance: Checks whether the first state state1 is dominated or equal to the second state state2.
isDominatedOrEqual(SMICState, SMICState) - Method in class org.ddolib.examples.smic.SMICDominance: Determines whether one state is dominated by or equal to another.
isDominatedOrEqual(TSPTWState, TSPTWState) - Method in class org.ddolib.examples.tsptw.TSPTWDominance: Checks whether state1 is dominated by or equal to state2.
isDominatedOrEqual(T, T) - Method in interface org.ddolib.modeling.Dominance: Tests whether state1 is dominated by or equivalent to state2.
isEmpty() - Method in interface org.ddolib.ddo.core.frontier.Frontier: Checks whether the frontier is empty.
isExact() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram: Indicates whether the compiled decision diagram is exact.
isExact() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Returns whether the decision diagram is exact.
isExplored() - Method in class org.ddolib.ddo.core.cache.Threshold: Returns whether the state has been explored.
isInExactCutSet - Variable in class org.ddolib.ddo.core.mdd.Node: Flag indicating if the node is in the exact cutset.
isMarked - Variable in class org.ddolib.ddo.core.mdd.Node: Flag indicating if the node is marked.

J

j - Variable in class org.ddolib.examples.max2sat.BinaryClause
jaccardDistance(BitSet, BitSet) - Static method in class org.ddolib.util.DistanceUtil: Computes the Jaccard Distance between the two given sets.

K

KSAcsMain - Class in org.ddolib.examples.knapsack: Knapsack Problem (KS) with Acs.
KSAcsMain() - Constructor for class org.ddolib.examples.knapsack.KSAcsMain
KSAlgo - Class in org.ddolib.examples.knapsack: Utility class providing algorithms to solve the Knapsack Problem.
KSAlgo() - Constructor for class org.ddolib.examples.knapsack.KSAlgo
KSAstarMain - Class in org.ddolib.examples.knapsack: Knapsack Problem (KS) with AsTar.
KSAstarMain() - Constructor for class org.ddolib.examples.knapsack.KSAstarMain
KSDdoMain - Class in org.ddolib.examples.knapsack: Knapsack Problem (KS) with Ddo.
KSDdoMain() - Constructor for class org.ddolib.examples.knapsack.KSDdoMain
KSDdoMainWithCluster - Class in org.ddolib.examples.knapsack: Knapsack Problem (KS) with Ddo.
KSDdoMainWithCluster() - Constructor for class org.ddolib.examples.knapsack.KSDdoMainWithCluster
KSDistance - Class in org.ddolib.examples.knapsack: Distance measure for states in a Knapsack (KS) problem.
KSDistance(KSProblem) - Constructor for class org.ddolib.examples.knapsack.KSDistance: Constructs a distance measure for a given Knapsack problem instance.
KSDominance - Class in org.ddolib.examples.knapsack: Dominance relation for the Knapsack Problem (KS).
KSDominance() - Constructor for class org.ddolib.examples.knapsack.KSDominance
KSFastLowerBound - Class in org.ddolib.examples.knapsack: Fast lower bound heuristic for the Knapsack Problem (KS).
KSFastLowerBound(KSProblem) - Constructor for class org.ddolib.examples.knapsack.KSFastLowerBound: Constructs a new fast lower bound heuristic for the given Knapsack problem.
KSLnsMain - Class in org.ddolib.examples.knapsack: Entry point for solving the 0/1 Knapsack Problem (KS) using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
KSLnsMain() - Constructor for class org.ddolib.examples.knapsack.KSLnsMain
KSProblem - Class in org.ddolib.examples.knapsack: Represents an instance of the Knapsack Problem (KS).
KSProblem(int, int[], int[]) - Constructor for class org.ddolib.examples.knapsack.KSProblem: Constructs a Knapsack problem with given capacity, profits, and weights.
KSProblem(int, int[], int[], double) - Constructor for class org.ddolib.examples.knapsack.KSProblem: Constructs a Knapsack problem with given capacity, profits, weights, and known optimal value.
KSProblem(String) - Constructor for class org.ddolib.examples.knapsack.KSProblem: Constructs a Knapsack problem from a file.
KSRanking - Class in org.ddolib.examples.knapsack: State ranking for the Knapsack Problem (KS).
KSRanking() - Constructor for class org.ddolib.examples.knapsack.KSRanking
KSRelax - Class in org.ddolib.examples.knapsack: Relaxation for the Knapsack Problem (KS).
KSRelax() - Constructor for class org.ddolib.examples.knapsack.KSRelax

L

LARGE - Enum constant in enum class org.ddolib.util.verbosity.VerbosityLevel: Displays detailed runtime information for debugging or analysis purposes.
LastExactLayer - Enum constant in enum class org.ddolib.ddo.core.frontier.CutSetType: The cut set corresponds to the last layer of the search space that can be evaluated exactly before approximations are applied.
latestToEarliestAircraftByClass - Variable in class org.ddolib.examples.alp.ALPProblem: Used to know which aircraft of each class will be next to land.
Layer() - Constructor for class org.ddolib.ddo.core.cache.SimpleCache.Layer
lb - Variable in class org.ddolib.ddo.core.mdd.NodeSubProblem: The lower bound associated with this node (root to terminal node)
LCSAcsMain - Class in org.ddolib.examples.lcs: Longest Common Subsequence (LCS) with Acs.
LCSAcsMain() - Constructor for class org.ddolib.examples.lcs.LCSAcsMain
LCSAstarMain - Class in org.ddolib.examples.lcs: Longest Common Subsequence (LCS) with AsTar.
LCSAstarMain() - Constructor for class org.ddolib.examples.lcs.LCSAstarMain
LCSDdoMain - Class in org.ddolib.examples.lcs: Longest Common Subsequence (LCS) with Ddo.
LCSDdoMain() - Constructor for class org.ddolib.examples.lcs.LCSDdoMain
LCSDp - Class in org.ddolib.examples.lcs: Naive DP solver the 2-strings longest common subsequence problem, used to build a heuristic for the m-strings problem.
LCSFastLowerBound - Class in org.ddolib.examples.lcs: Implementation of a fast lower bound heuristic for the Longest Common Subsequence (LCS) problem.
LCSFastLowerBound(LCSProblem) - Constructor for class org.ddolib.examples.lcs.LCSFastLowerBound: Constructs a fast lower bound heuristic for a given LCS problem.
LCSGenerator - Class in org.ddolib.examples.lcs: Contains method to generate instances of the LCS
LCSGenerator() - Constructor for class org.ddolib.examples.lcs.LCSGenerator
LCSLnsMain - Class in org.ddolib.examples.lcs: Entry point for solving the Longest Common Subsequence (LCS) problem using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
LCSLnsMain() - Constructor for class org.ddolib.examples.lcs.LCSLnsMain
LCSProblem - Class in org.ddolib.examples.lcs: Definition of the Longest Common Subsequence (LCS) problem.
LCSProblem(String) - Constructor for class org.ddolib.examples.lcs.LCSProblem: Constructs an LCS problem instance from a file.
LCSProblem(String, int, int, int[][], int[], int[][][], int[][][], HashMap<Character, Integer>, Character[], Optional<Double>) - Constructor for class org.ddolib.examples.lcs.LCSProblem: Constructs an LCS problem instance with all precomputed structures.
LCSRanking - Class in org.ddolib.examples.lcs: Ranking strategy for LCSState in the Longest Common Subsequence (LCS) problem.
LCSRanking() - Constructor for class org.ddolib.examples.lcs.LCSRanking
LCSRelax - Class in org.ddolib.examples.lcs: Relaxation strategy for LCSState in the Longest Common Subsequence (LCS) problem.
LCSRelax(LCSProblem) - Constructor for class org.ddolib.examples.lcs.LCSRelax: Constructs a relaxation object for a given LCS problem.
LCSState - Class in org.ddolib.examples.lcs: Represents the state of a node in the Longest Common Subsequence (LCS) problem.
LinkedDecisionDiagram<T> - Class in org.ddolib.ddo.core.mdd: This class implements a decision diagram as a linked structure (linked MDD).
LinkedDecisionDiagram(CompilationConfig<T>) - Constructor for class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Creates a new linked decision diagram.
LnsModel<T> - Interface in org.ddolib.modeling: Interface representing a model for Large Neighborhood Search (LNS) problems.
LNSSolver<T> - Class in org.ddolib.lns.core.solver
LNSSolver(LnsModel<T>) - Constructor for class org.ddolib.lns.core.solver.LNSSolver
lowerBound() - Method in interface org.ddolib.modeling.Model: Returns a heuristic that estimates a lower bound on the objective value for a given state.
lowerBoundForAllSubsets(int[][]) - Static method in class org.ddolib.util.TSPLowerBound: Computes a lower-bound for all subsets of a set of nodes based on the given cost matrix.

M

main(String[]) - Static method in class org.ddolib.examples.alp.ALPAcsMain
main(String[]) - Static method in class org.ddolib.examples.alp.ALPAstarMain
main(String[]) - Static method in class org.ddolib.examples.alp.ALPDdoMain
main(String[]) - Static method in class org.ddolib.examples.alp.ALPLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.boundedknapsack.BKSAcsMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.boundedknapsack.BKSAstarMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.boundedknapsack.BKSDdoMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.boundedknapsack.BKSLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.gruler.GRAcsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.gruler.GRAstarMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.gruler.GRDdoMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.knapsack.KSAcsMain: Entry point of the ACS demonstration for the Knapsack Problem.
main(String[]) - Static method in class org.ddolib.examples.knapsack.KSAstarMain: Entry point of the A* demonstration for the Knapsack Problem.
main(String[]) - Static method in class org.ddolib.examples.knapsack.KSDdoMain: Entry point of the DDO demonstration for the Knapsack Problem.
main(String[]) - Static method in class org.ddolib.examples.knapsack.KSDdoMainWithCluster: Entry point of the DDO demonstration for the Knapsack Problem.
main(String[]) - Static method in class org.ddolib.examples.knapsack.KSLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.lcs.LCSAcsMain
main(String[]) - Static method in class org.ddolib.examples.lcs.LCSAstarMain
main(String[]) - Static method in class org.ddolib.examples.lcs.LCSDdoMain
main(String[]) - Static method in class org.ddolib.examples.lcs.LCSGenerator
main(String[]) - Static method in class org.ddolib.examples.lcs.LCSLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.max2sat.Max2SatAcsMain: Main entry point for the MAX2SAT Ant Colony System solver.
main(String[]) - Static method in class org.ddolib.examples.max2sat.Max2SatAstarMain: Main entry point for executing the A* search on a MAX2SAT instance.
main(String[]) - Static method in class org.ddolib.examples.max2sat.Max2SatDdoMain: Main entry point for executing the DDO algorithm on a MAX2SAT instance.
main(String[]) - Static method in class org.ddolib.examples.max2sat.Max2SatGenerator
main(String[]) - Static method in class org.ddolib.examples.max2sat.Max2SatLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.maximumcoverage.MaxCoverDdoMain: Program entry point.
main(String[]) - Static method in class org.ddolib.examples.maximumcoverage.MaxCoverDdoMainWithCluster
main(String[]) - Static method in class org.ddolib.examples.maximumcoverage.MaxCoverGenerator: Program entry point.
main(String[]) - Static method in class org.ddolib.examples.maximumcoverage.MaxCoverLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.mcp.MCPAcsMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.mcp.MCPAstarMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.mcp.MCPDdoMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.mcp.MCPLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.misp.MispAcsMain: Main method to execute the ACS solver on a given MISP instance.
main(String[]) - Static method in class org.ddolib.examples.misp.MispAstarMain: Main method to execute the A* solver on a MISP instance.
main(String[]) - Static method in class org.ddolib.examples.misp.MispAwAstarMain: Main method to execute the AWA* solver on a MISP instance.
main(String[]) - Static method in class org.ddolib.examples.misp.MispDdoMain: Main method to execute the DDO solver on a MISP instance.
main(String[]) - Static method in class org.ddolib.examples.misp.MispGenerator
main(String[]) - Static method in class org.ddolib.examples.misp.MispLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.mks.MKSDDoMain: Entry point for the DDO demonstration.
main(String[]) - Static method in class org.ddolib.examples.msct.MSCTAcsMain: Entry point for running the ACS solver on an MSCT instance.
main(String[]) - Static method in class org.ddolib.examples.msct.MSCTAstarMain: Entry point for running the A* solver on an MSCT instance.
main(String[]) - Static method in class org.ddolib.examples.msct.MSCTDdoMain: Entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.msct.MSCTGenerator
main(String[]) - Static method in class org.ddolib.examples.msct.MSCTLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.pdp.PDPAcsMain: Entry point for the PDP ACS solver.
main(String[]) - Static method in class org.ddolib.examples.pdp.PDPAstarMain: Entry point for solving a randomly generated Pickup and Delivery Problem (PDP) instance using the A* algorithm.
main(String[]) - Static method in class org.ddolib.examples.pdp.PDPDdoMain: Entry point for solving a randomly generated Pickup and Delivery Problem (PDP) instance using the Dynamic Decision Diagram Optimization (DDO) method.
main(String[]) - Static method in class org.ddolib.examples.pdp.PDPLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.pigmentscheduling.PSAcsMain: Entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.pigmentscheduling.PSAstarMain: Entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.pigmentscheduling.PSDdoMain: Entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.pigmentscheduling.PSLnsMain: Main entry point of the program.
main(String[]) - Static method in class org.ddolib.examples.smic.SMICAcsMain: Entry point of the SMIC Anytime Column Search solver.
main(String[]) - Static method in class org.ddolib.examples.smic.SMICAstarMain: Entry point of the SMIC A* solver.
main(String[]) - Static method in class org.ddolib.examples.smic.SMICDdoMain: Entry point of the SMIC solver using the Dynamic Decision Diagram Optimization (DDO) algorithm.
main(String[]) - Static method in class org.ddolib.examples.smic.SMICLnsMain: Main method to run the SMIC LNS solver.
main(String[]) - Static method in class org.ddolib.examples.srflp.SRFLPAcsMain
main(String[]) - Static method in class org.ddolib.examples.srflp.SRFLPAstarMain
main(String[]) - Static method in class org.ddolib.examples.srflp.SRFLPDdoMain
main(String[]) - Static method in class org.ddolib.examples.srflp.SRFLPLnsMain: Main method to run the SRFLP LNS solver.
main(String[]) - Static method in class org.ddolib.examples.talentscheduling.TSAcsMain
main(String[]) - Static method in class org.ddolib.examples.talentscheduling.TSAstarMain
main(String[]) - Static method in class org.ddolib.examples.talentscheduling.TSDdoMain
main(String[]) - Static method in class org.ddolib.examples.talentscheduling.TSLnsMain: Main method to run the Talent Scheduling LNS solver.
main(String[]) - Static method in class org.ddolib.examples.tsp.TSPAcsMain
main(String[]) - Static method in class org.ddolib.examples.tsp.TSPAstarMain
main(String[]) - Static method in class org.ddolib.examples.tsp.TSPDdoMain
main(String[]) - Static method in class org.ddolib.examples.tsp.TSPLnsMain: Main method to run the TSP LNS solver.
main(String[]) - Static method in class org.ddolib.examples.tsptw.TSPTWAcsMain: Entry point for running the ACS solver on a TSPTW instance.
main(String[]) - Static method in class org.ddolib.examples.tsptw.TSPTWAstarMain: Entry point for running the A* solver on a TSPTW instance.
main(String[]) - Static method in class org.ddolib.examples.tsptw.TSPTWAwAstarMain: Entry point for running the A* solver on a TSPTW instance.
main(String[]) - Static method in class org.ddolib.examples.tsptw.TSPTWDdoMain: Entry point of the application.
main(String[]) - Static method in class org.ddolib.examples.tsptw.TSPTWLnsMain: Main method to run the TSPTW LNS solver.
MathUtil - Class in org.ddolib.util: Utility class providing mathematical operations with saturation semantics.
MathUtil() - Constructor for class org.ddolib.util.MathUtil
Max2SatAcsMain - Class in org.ddolib.examples.max2sat: Maximum 2-Satisfiability (MAX2SAT) (MAX2SAT) problem with Acs.
Max2SatAcsMain() - Constructor for class org.ddolib.examples.max2sat.Max2SatAcsMain
Max2SatAstarMain - Class in org.ddolib.examples.max2sat: Maximum 2-Satisfiability (MAX2SAT) (MAX2SAT) problem with AsTar.
Max2SatAstarMain() - Constructor for class org.ddolib.examples.max2sat.Max2SatAstarMain
Max2SatDdoMain - Class in org.ddolib.examples.max2sat: Maximum 2-Satisfiability (MAX2SAT) (MAX2SAT) problem with Ddo.
Max2SatDdoMain() - Constructor for class org.ddolib.examples.max2sat.Max2SatDdoMain
Max2SatFastLowerBound - Class in org.ddolib.examples.max2sat: Implementation of a fast lower bound heuristic for the Maximum 2-Satisfiability (MAX2SAT) problem.
Max2SatFastLowerBound(Max2SatProblem) - Constructor for class org.ddolib.examples.max2sat.Max2SatFastLowerBound: Constructs the fast lower bound for a given MAX2SAT problem instance.
Max2SatGenerator - Class in org.ddolib.examples.max2sat: Methods to generate random instance of the Max2Sat problem.
Max2SatGenerator() - Constructor for class org.ddolib.examples.max2sat.Max2SatGenerator
Max2SatLnsMain - Class in org.ddolib.examples.max2sat: Entry point for solving the Maximum 2-Satisfiability (MAX-2SAT) problem using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
Max2SatLnsMain() - Constructor for class org.ddolib.examples.max2sat.Max2SatLnsMain
Max2SatProblem - Class in org.ddolib.examples.max2sat: Represents a Maximum 2-Satisfiability (MAX2SAT) problem instance.
Max2SatProblem(int, HashMap<BinaryClause, Integer>) - Constructor for class org.ddolib.examples.max2sat.Max2SatProblem: Constructs a MAX2SAT problem instance without specifying an optimal value.
Max2SatProblem(int, HashMap<BinaryClause, Integer>, Optional<Double>) - Constructor for class org.ddolib.examples.max2sat.Max2SatProblem: Constructs a MAX2SAT problem instance.
Max2SatProblem(String) - Constructor for class org.ddolib.examples.max2sat.Max2SatProblem: Constructs a MAX2SAT problem instance from a file.
Max2SatRanking - Class in org.ddolib.examples.max2sat: Class used to compare two states for the Max2Sat problem.
Max2SatRanking() - Constructor for class org.ddolib.examples.max2sat.Max2SatRanking
Max2SatRelax - Class in org.ddolib.examples.max2sat: Implements a relaxation for the Maximum 2-Satisfiability (MAX2SAT) problem.
Max2SatRelax(Max2SatProblem) - Constructor for class org.ddolib.examples.max2sat.Max2SatRelax: Constructs a relaxation for the given MAX2SAT problem.
Max2SatState - Record Class in org.ddolib.examples.max2sat: Class to contain data for the Max2Sat sate.
Max2SatState(ArrayList<Integer>, int) - Constructor for record class org.ddolib.examples.max2sat.Max2SatState: Creates an instance of a Max2SatState record class.
maxCapa - Variable in class org.ddolib.examples.pdp.PDPProblem: Maximum capacity of the vehicle.
MaxCoverDdoMain - Class in org.ddolib.examples.maximumcoverage: Maximum Coverage (MaxCover) problem with Ddo
MaxCoverDdoMain() - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverDdoMain
MaxCoverDdoMainWithCluster - Class in org.ddolib.examples.maximumcoverage: Maximum Coverage (MaxCover) problem with Ddo
MaxCoverDdoMainWithCluster() - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverDdoMainWithCluster
MaxCoverDistance - Class in org.ddolib.examples.maximumcoverage: Distance function for MaxCoverState used to measure similarity between states in the context of the Maximum Coverage problem.
MaxCoverDistance(MaxCoverProblem) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverDistance: Constructs a distance measure associated with a given MaxCover problem instance.
MaxCoverDominance - Class in org.ddolib.examples.maximumcoverage: Dominance rule for MaxCoverState used in the Maximum Coverage problem.
MaxCoverDominance() - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverDominance
MaxCoverFastLowerBound - Class in org.ddolib.examples.maximumcoverage: Fast lower bound computation for the Maximum Coverage problem.
MaxCoverFastLowerBound(MaxCoverProblem) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverFastLowerBound: Constructs a fast lower bound evaluator for a given MaxCover problem.
MaxCoverGenerator - Class in org.ddolib.examples.maximumcoverage: Utility class for generating and measuring instances of the Maximum Coverage (MaxCover) problem.
MaxCoverGenerator() - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverGenerator
MaxCoverLnsMain - Class in org.ddolib.examples.maximumcoverage: Entry point for solving the Maximum Coverage (MaxCover) problem using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
MaxCoverLnsMain() - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverLnsMain
MaxCoverProblem - Class in org.ddolib.examples.maximumcoverage: Represents an instance of the Maximum Coverage (MaxCover) problem.
MaxCoverProblem(int, int, int, double, int) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Generates a random MaxCover instance using coordinates and a distance threshold.
MaxCoverProblem(int, int, int, BitSet[]) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Constructs a MaxCover instance without name or optimal value.
MaxCoverProblem(int, int, int, BitSet[], Optional<Double>) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Constructs a MaxCover instance without a name.
MaxCoverProblem(String) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Loads a MaxCover instance from a file.
MaxCoverProblem(Optional<String>, int, int, int, BitSet[], Optional<Double>) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Constructs a MaxCover instance with full specification.
MaxCoverRanking - Class in org.ddolib.examples.maximumcoverage: Ranking function for MaxCoverState used in the Maximum Coverage problem.
MaxCoverRanking() - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverRanking
MaxCoverRelax - Class in org.ddolib.examples.maximumcoverage: Relaxation operator for MaxCoverState in the Maximum Coverage problem.
MaxCoverRelax(MaxCoverProblem) - Constructor for class org.ddolib.examples.maximumcoverage.MaxCoverRelax: Constructs a MaxCover relaxation operator for a given problem instance.
MaxCoverState - Record Class in org.ddolib.examples.maximumcoverage: Represents a state in the Maximum Coverage (MaxCover) problem.
MaxCoverState(BitSet) - Constructor for record class org.ddolib.examples.maximumcoverage.MaxCoverState: Creates an instance of a MaxCoverState record class.
maxCurrentInventory() - Method in record class org.ddolib.examples.smic.SMICState: Returns the value of the maxCurrentInventory record component.
maximize() - Method in class org.ddolib.examples.max2sat.NaiveMax2SatSolver
maximize() - Method in class org.ddolib.examples.mcp.NaiveMCPSolver
maximumWidth(TSPTWState) - Method in class org.ddolib.examples.tsptw.TSPTWWidth: Computes the maximum width of a layer based on the current state.
maximumWidth(T) - Method in class org.ddolib.ddo.core.heuristics.width.FixedWidth: Returns the maximum width for the given state.
maximumWidth(T) - Method in interface org.ddolib.ddo.core.heuristics.width.WidthHeuristic: Computes the maximum width allowed for a layer rooted at the given state.
maxWidth - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Maximum allowed width (number of nodes) per layer in the MDD.
maybe() - Method in record class org.ddolib.examples.srflp.SRFLPState: Returns the value of the maybe record component.
maybeScenes() - Method in record class org.ddolib.examples.talentscheduling.TSState: Returns the value of the maybeScenes record component.
MCPAcsMain - Class in org.ddolib.examples.mcp: Maximum Cut Problem (MCP) with Acs.
MCPAcsMain() - Constructor for class org.ddolib.examples.mcp.MCPAcsMain
MCPAstarMain - Class in org.ddolib.examples.mcp: Maximum Cut Problem (MCP) with AsTar.
MCPAstarMain() - Constructor for class org.ddolib.examples.mcp.MCPAstarMain
MCPDdoMain - Class in org.ddolib.examples.mcp: Main class for solving the Maximum Cut Problem (MCP) using a DDO (Decision Diagram Optimization) approach.
MCPDdoMain() - Constructor for class org.ddolib.examples.mcp.MCPDdoMain
MCPFastLowerBound - Class in org.ddolib.examples.mcp: Implementation of fast lower bound heuristic for the MCP.
MCPFastLowerBound(MCPProblem) - Constructor for class org.ddolib.examples.mcp.MCPFastLowerBound
MCPGenerator - Class in org.ddolib.examples.mcp: Contains methods to generates and write instances.
MCPGenerator() - Constructor for class org.ddolib.examples.mcp.MCPGenerator
MCPLnsMain - Class in org.ddolib.examples.mcp: Entry point for solving the Maximum Cut Problem (MCP) using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
MCPLnsMain() - Constructor for class org.ddolib.examples.mcp.MCPLnsMain
MCPProblem - Class in org.ddolib.examples.mcp: Represents an instance of the Maximum Cut Problem (MCP).
MCPProblem(String) - Constructor for class org.ddolib.examples.mcp.MCPProblem: Constructs an MCP problem by reading an instance from a file.
MCPProblem(Graph) - Constructor for class org.ddolib.examples.mcp.MCPProblem: Constructs an MCP problem from a given graph.
MCPProblem(Graph, Double) - Constructor for class org.ddolib.examples.mcp.MCPProblem: Constructs an MCP problem from a given graph and known optimal value.
MCPRanking - Class in org.ddolib.examples.mcp: Class used to compare two states for the MCP problem.
MCPRanking() - Constructor for class org.ddolib.examples.mcp.MCPRanking
MCPRelax - Class in org.ddolib.examples.mcp: Implements a relaxation strategy for the Maximum Cut Problem (MCP).
MCPRelax(MCPProblem) - Constructor for class org.ddolib.examples.mcp.MCPRelax: Constructs a relaxation for the given MCP problem.
MCPState - Record Class in org.ddolib.examples.mcp: Class to contain data for the MCP state.
MCPState(ArrayList<Integer>, int) - Constructor for record class org.ddolib.examples.mcp.MCPState: Creates an instance of a MCPState record class.
mergeStates(Iterator<Integer>) - Method in class org.ddolib.examples.boundedknapsack.BKSRelax: Merges a set of states into a single representative state for a relaxed DD.
mergeStates(Iterator<Integer>) - Method in class org.ddolib.examples.knapsack.KSRelax: Merges multiple states into a single relaxed state.
mergeStates(Iterator<BitSet>) - Method in class org.ddolib.examples.misp.MispRelax: Merges multiple states into a single relaxed state.
mergeStates(Iterator<ALPState>) - Method in class org.ddolib.examples.alp.ALPRelax: Merges multiple states into a single relaxed state.
mergeStates(Iterator<GRState>) - Method in class org.ddolib.examples.gruler.GRRelax: Merges several GRState objects into a single relaxed state.
mergeStates(Iterator<LCSState>) - Method in class org.ddolib.examples.lcs.LCSRelax: Merges multiple LCS states into a single relaxed state.
mergeStates(Iterator<Max2SatState>) - Method in class org.ddolib.examples.max2sat.Max2SatRelax: Merges multiple Max2SatState instances into a single relaxed state.
mergeStates(Iterator<MaxCoverState>) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverRelax: Merges a collection of states into a single relaxed state.
mergeStates(Iterator<MCPState>) - Method in class org.ddolib.examples.mcp.MCPRelax: Merges multiple MCP states into a single optimistic state.
mergeStates(Iterator<MKSState>) - Method in class org.ddolib.examples.mks.MKSRelax: Merges multiple MKS states into a single relaxed state.
mergeStates(Iterator<MSCTState>) - Method in class org.ddolib.examples.msct.MSCTRelax: Merges several MSCTState objects into a single relaxed state.
mergeStates(Iterator<PSState>) - Method in class org.ddolib.examples.pigmentscheduling.PSRelax: Merges multiple PSP states into a single relaxed state.
mergeStates(Iterator<SMICState>) - Method in class org.ddolib.examples.smic.SMICRelax: Merges several SMICState objects into a single relaxed state.
mergeStates(Iterator<SRFLPState>) - Method in class org.ddolib.examples.srflp.SRFLPRelax: Merges multiple SRFLP states into a single relaxed state.
mergeStates(Iterator<TSState>) - Method in class org.ddolib.examples.talentscheduling.TSRelax: Merges multiple TSState instances into a single relaxed state.
mergeStates(Iterator<TSPState>) - Method in class org.ddolib.examples.tsp.TSPRelax: Merges multiple TSPState instances into a single relaxed state.
mergeStates(Iterator<TSPTWState>) - Method in class org.ddolib.examples.tsptw.TSPTWRelax: Merges multiple TSPTW states into a single relaxed state.
mergeStates(Iterator<T>) - Method in interface org.ddolib.modeling.Relaxation: Merges the given states to create a NEW state which is an over approximation of all the covered states.
minCurrentInventory() - Method in record class org.ddolib.examples.smic.SMICState: Returns the value of the minCurrentInventory record component.
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.acs.core.solver.ACSSolver: Minimizes the problem using the ACS strategy.
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.astar.core.solver.AStarSolver
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.awastar.core.solver.AwAstarSolver
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in interface org.ddolib.common.solver.Solver: Minimizes the objective function according to the solver strategy.
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.ddo.core.solver.ExactSolver: Minimizes the problem by compiling an exact decision diagram (MDD).
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.ddo.core.solver.RelaxationSolver
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.ddo.core.solver.RestrictionSolver
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.ddo.core.solver.SequentialSolver
minimize(Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Method in class org.ddolib.lns.core.solver.LNSSolver
minimizeAcs(AcsModel<T>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using the Anytime Column Search (ACS) algorithm.
minimizeAcs(AcsModel<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using ACS and calls the callback when a new incumbent is found.
minimizeAcs(AcsModel<T>, Predicate<SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using ACS, stopping when the limit condition is satisfied.
minimizeAcs(AcsModel<T>, Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Core method for solving an ACS model with custom stopping condition and solution callback.
minimizeAstar(Model<T>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using the A* search algorithm with default parameters.
minimizeAstar(Model<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using A* and calls back when new incumbent solutions are found.
minimizeAstar(Model<T>, Predicate<SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using A* with a specified stop condition.
minimizeAstar(Model<T>, Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Core method for solving a model with the A* search algorithm, with custom limit and callback.
minimizeAwAStar(AwAstarModel<T>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using the Anytime Weighted A* (AWA*) algorithm.
minimizeAwAStar(AwAstarModel<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using AWA* and calls the callback when a new incumbent is found.
minimizeAwAStar(AwAstarModel<T>, Predicate<SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using AWA*, stopping when the limit condition is satisfied.
minimizeAwAStar(AwAstarModel<T>, Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Core method for solving a model with the Anytime Weighted A* search algorithm, with custom limit and callback.
minimizeDdo(DdoModel<T>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using the DDO (Decision Diagram Optimization) algorithm with default stopping criteria and no solution callback.
minimizeDdo(DdoModel<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using DDO and triggers a callback each time a new incumbent solution is found.
minimizeDdo(DdoModel<T>, Predicate<SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using DDO, stopping when the provided limit condition becomes true.
minimizeDdo(DdoModel<T>, Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Core method for solving a DDO model with a custom stop condition and a solution callback.
minimizeExact(ExactModel<T>) - Static method in class org.ddolib.modeling.Solvers: Solves the given model using the Exact DDO algorithm.
minimizeExact(ExactModel<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Core method for solving an DDO model with solution callback.
minimizeLns(LnsModel<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Runs a Large Neighborhood Search (LNS) on the specified model without any termination condition and without processing intermediate solutions.
minimizeLns(LnsModel<T>, Predicate<SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Runs a Large Neighborhood Search (LNS) on the specified model with a termination condition but without processing intermediate solutions.
minimizeLns(LnsModel<T>, Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers: Runs a Large Neighborhood Search (LNS) on the specified model with a given termination condition and a callback for each solution found.
minLowerBound() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram
minLowerBound() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Returns the minimum lower bound of expanded nodes of the MDD during the LNS compilation.
MispAcsMain - Class in org.ddolib.examples.misp: The Maximum Independent Set Problem (MISP) with Acs.
MispAcsMain() - Constructor for class org.ddolib.examples.misp.MispAcsMain
MispAstarMain - Class in org.ddolib.examples.misp: The Maximum Independent Set Problem (MISP) with AsTar.
MispAstarMain() - Constructor for class org.ddolib.examples.misp.MispAstarMain
MispAwAstarMain - Class in org.ddolib.examples.misp: The Maximum Independent Set Problem (MISP) with Anytime Weighted A* (AWA*).
MispAwAstarMain() - Constructor for class org.ddolib.examples.misp.MispAwAstarMain
MispDdoMain - Class in org.ddolib.examples.misp: The Maximum Independent Set Problem (MISP) with Ddo.
MispDdoMain() - Constructor for class org.ddolib.examples.misp.MispDdoMain
MispDominance - Class in org.ddolib.examples.misp: Implementation of a dominance relation for the Maximum Independent Set Problem (MISP).
MispDominance() - Constructor for class org.ddolib.examples.misp.MispDominance
MispFastLowerBound - Class in org.ddolib.examples.misp: Computes a fast lower bound for the Maximum Independent Set Problem (MISP).
MispFastLowerBound(MispProblem) - Constructor for class org.ddolib.examples.misp.MispFastLowerBound: Constructs a fast lower bound calculator for a given MISP problem.
MispGenerator - Class in org.ddolib.examples.misp: Contains methods to generate instances of the MISP.
MispGenerator() - Constructor for class org.ddolib.examples.misp.MispGenerator
MispLnsMain - Class in org.ddolib.examples.misp: Entry point for solving the Maximum Independent Set Problem (MISP) using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
MispLnsMain() - Constructor for class org.ddolib.examples.misp.MispLnsMain
MispProblem - Class in org.ddolib.examples.misp: Represents an instance of the Maximum Independent Set Problem (MISP) as a Problem.
MispProblem(String) - Constructor for class org.ddolib.examples.misp.MispProblem: Loads a MISP problem from a DOT file.
MispProblem(BitSet, BitSet[], int[]) - Constructor for class org.ddolib.examples.misp.MispProblem: Constructs a MISP problem with a given state, adjacency lists, and weights.
MispProblem(BitSet, BitSet[], int[], double) - Constructor for class org.ddolib.examples.misp.MispProblem: Constructs a MISP problem with a given state, adjacency lists, weights, and known optimal value.
MispRanking - Class in org.ddolib.examples.misp: Implements a ranking strategy for states in the Maximum Independent Set Problem (MISP).
MispRanking() - Constructor for class org.ddolib.examples.misp.MispRanking
MispRelax - Class in org.ddolib.examples.misp: Implements a relaxation strategy for the Maximum Independent Set Problem (MISP) to be used in decision diagram optimization (DDO) algorithms.
MispRelax(MispProblem) - Constructor for class org.ddolib.examples.misp.MispRelax: Constructs a relaxation for the given MISP problem instance.
MKSDDoMain - Class in org.ddolib.examples.mks: Main class to demonstrate the application of Decision Diagram Optimization (DDO) on a Multi-dimensional Knapsack (MKS) problem instance.
MKSDDoMain() - Constructor for class org.ddolib.examples.mks.MKSDDoMain
MKSDistance - Class in org.ddolib.examples.mks: Computes a normalized distance between Multi-dimensional Knapsack (MKS) states.
MKSDistance(MKSProblem) - Constructor for class org.ddolib.examples.mks.MKSDistance: Constructs a distance evaluator for the given MKS problem.
MKSDominance - Class in org.ddolib.examples.mks: Implements a dominance relation for Multi-dimensional Knapsack (MKS) states.
MKSDominance() - Constructor for class org.ddolib.examples.mks.MKSDominance
MKSFastLowerBound - Class in org.ddolib.examples.mks: Provides a fast lower bound estimation for Multi-dimensional Knapsack (MKS) states.
MKSFastLowerBound(MKSProblem) - Constructor for class org.ddolib.examples.mks.MKSFastLowerBound: Constructs a fast lower bound evaluator for the given MKS problem.
MKSProblem - Class in org.ddolib.examples.mks: Represents a Multi-dimensional Knapsack Problem (MKS) as a Problem for decision diagram optimization.
MKSProblem(double[], int[], int[][], double) - Constructor for class org.ddolib.examples.mks.MKSProblem: Constructs an MKSProblem with the given capacities, profits, and weights.
MKSProblem(String) - Constructor for class org.ddolib.examples.mks.MKSProblem: Loads an MKSProblem from a text file.
MKSRanking - Class in org.ddolib.examples.mks: Ranking strategy for multi-dimensional Knapsack (MKS) states.
MKSRanking() - Constructor for class org.ddolib.examples.mks.MKSRanking
MKSRelax - Class in org.ddolib.examples.mks: Relaxation strategy for the multi-dimensional Knapsack problem (MKS) states.
MKSRelax() - Constructor for class org.ddolib.examples.mks.MKSRelax
MKSState - Class in org.ddolib.examples.mks: Represents the state of a multi-dimensional Knapsack problem (MKS) in terms of the remaining capacities of each knapsack dimension.
MKSState(double[]) - Constructor for class org.ddolib.examples.mks.MKSState: Constructs a new MKSState with the given capacities.
Model<T> - Interface in org.ddolib.modeling: Defines the core model interface for describing an optimization problem to be solved within the Decision Diagram Optimization (DDO) framework.
Model Components - Search tag in class org.ddolib.examples.alp.ALPLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.boundedknapsack.BKSLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.knapsack.KSLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.lcs.LCSLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.max2sat.Max2SatLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.maximumcoverage.MaxCoverLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.mcp.MCPLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.misp.MispLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.msct.MSCTLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.pdp.PDPLnsMain: Section
Model Components - Search tag in class org.ddolib.examples.pigmentscheduling.PSLnsMain: Section
MSCTAcsMain - Class in org.ddolib.examples.msct: Minimum Sum Completion Time (MSCT) with Acs.
MSCTAcsMain() - Constructor for class org.ddolib.examples.msct.MSCTAcsMain
MSCTAstarMain - Class in org.ddolib.examples.msct: Minimum Sum Completion Time (MSCT) with AsTar.
MSCTAstarMain() - Constructor for class org.ddolib.examples.msct.MSCTAstarMain
MSCTDdoMain - Class in org.ddolib.examples.msct: Minimum Sum Completion Time (MSCT) with Ddo.
MSCTDdoMain() - Constructor for class org.ddolib.examples.msct.MSCTDdoMain
MSCTDominance - Class in org.ddolib.examples.msct: Implements the dominance relation for the Maximum Sum of Compatible Tasks (MSCT) problem.
MSCTDominance() - Constructor for class org.ddolib.examples.msct.MSCTDominance
MSCTFastLowerBound - Class in org.ddolib.examples.msct: Provides a fast lower bound computation for the Maximum Sum of Compatible Tasks (MSCT) problem.
MSCTFastLowerBound(MSCTProblem) - Constructor for class org.ddolib.examples.msct.MSCTFastLowerBound: Constructs a lower bound evaluator for a specific instance of the MSCT problem.
MSCTGenerator - Class in org.ddolib.examples.msct: Contains methods to generates instance of the MSCT
MSCTGenerator() - Constructor for class org.ddolib.examples.msct.MSCTGenerator
MSCTLnsMain - Class in org.ddolib.examples.msct: Entry point for solving the Minimum Sum of Completion Times (MSCT) problem using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
MSCTLnsMain() - Constructor for class org.ddolib.examples.msct.MSCTLnsMain
MSCTProblem - Class in org.ddolib.examples.msct: Represents an instance of the **Minimum Sum of Completion Times (MSCT)** problem.
MSCTProblem(int) - Constructor for class org.ddolib.examples.msct.MSCTProblem: Constructs a randomly generated MSCT problem instance for testing purposes.
MSCTProblem(int[], int[]) - Constructor for class org.ddolib.examples.msct.MSCTProblem: Constructs an MSCT problem from explicit arrays of release and processing times, without specifying an optimal value.
MSCTProblem(int[], int[], Optional<Double>) - Constructor for class org.ddolib.examples.msct.MSCTProblem: Constructs an MSCT problem from explicit arrays of release and processing times, with an optional known optimal value.
MSCTProblem(String) - Constructor for class org.ddolib.examples.msct.MSCTProblem: Constructs an MSCT problem by reading data from a text file.
MSCTRanking - Class in org.ddolib.examples.msct: Provides a ranking strategy for MSCTState objects used in the search process for solving the Maximum Sum of Completion Times (MSCT) problem.
MSCTRanking() - Constructor for class org.ddolib.examples.msct.MSCTRanking
MSCTRelax - Class in org.ddolib.examples.msct: Implements the relaxation operator for the MSCTProblem in the context of Decision Diagram Optimization (DDO) algorithms.
MSCTRelax(MSCTProblem) - Constructor for class org.ddolib.examples.msct.MSCTRelax: Constructs a relaxation operator for the given MSCT problem instance.
MSCTState - Record Class in org.ddolib.examples.msct: Represents a state in the MSCTProblem (Minimum Sum of Completion Times) scheduling problem.
MSCTState(Set<Integer>, int) - Constructor for record class org.ddolib.examples.msct.MSCTState: Creates an instance of a MSCTState record class.
must() - Method in record class org.ddolib.examples.srflp.SRFLPState: Returns the value of the must record component.
mustExplore(SubProblem<T>, int) - Method in interface org.ddolib.ddo.core.cache.Cache: Determines whether the given subproblem must still be explored, based on the information currently stored in the cache.
mustVisit() - Method in record class org.ddolib.examples.tsptw.TSPTWDominanceKey: Returns the value of the mustVisit record component.
mustVisit() - Method in record class org.ddolib.examples.tsptw.TSPTWState: Returns the value of the mustVisit record component.

N

n - Variable in class org.ddolib.examples.pdp.PDPProblem: Number of nodes in the problem.
n - Variable in class org.ddolib.examples.tsp.TSPGenerator: Number of cities
NaiveMax2SatSolver - Class in org.ddolib.examples.max2sat: A naive Max2Sat solver which enumerates all the solution to find the best one.
NaiveMax2SatSolver(Max2SatProblem) - Constructor for class org.ddolib.examples.max2sat.NaiveMax2SatSolver
NaiveMCPSolver - Class in org.ddolib.examples.mcp: Naive MCP solver which enumerates all the solution to find the best one.
NaiveMCPSolver(MCPProblem) - Constructor for class org.ddolib.examples.mcp.NaiveMCPSolver
name - Variable in class org.ddolib.examples.knapsack.KSProblem: Optional name of the instance (usually the filename).
name - Variable in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Optional instance name.
nbAircraft - Variable in class org.ddolib.examples.alp.ALPProblem: Total number of aircraft.
nbClasses - Variable in class org.ddolib.examples.alp.ALPProblem: Number of aircraft classes.
nbHits - Variable in class org.ddolib.ddo.core.cache.SimpleCache.Layer: Number of cache hits.
nbItems - Variable in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Number of items in the instance.
nbIterations() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns the value of the nbIterations record component.
nbRunways - Variable in class org.ddolib.examples.alp.ALPProblem: Number of available runways.
nbSubSets - Variable in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Number of subsets in the instance.
nbSubSetsToChoose - Variable in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Number of subsets that can be selected.
nbTests - Variable in class org.ddolib.ddo.core.cache.SimpleCache.Layer: Number of queries to this layer.
nbVars() - Method in class org.ddolib.examples.alp.ALPProblem
nbVars() - Method in class org.ddolib.examples.boundedknapsack.BKSProblem: Returns the number of variables (items) in the knapsack.
nbVars() - Method in class org.ddolib.examples.gruler.GRProblem: Returns the number of variables in the problem.
nbVars() - Method in class org.ddolib.examples.knapsack.KSProblem
nbVars() - Method in class org.ddolib.examples.lcs.LCSProblem
nbVars() - Method in class org.ddolib.examples.max2sat.Max2SatProblem
nbVars() - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns the number of decision variables in the problem.
nbVars() - Method in class org.ddolib.examples.mcp.MCPProblem
nbVars() - Method in class org.ddolib.examples.misp.MispProblem
nbVars() - Method in class org.ddolib.examples.mks.MKSProblem: Returns the number of decision variables (items).
nbVars() - Method in class org.ddolib.examples.msct.MSCTProblem: Returns the number of jobs in this instance.
nbVars() - Method in class org.ddolib.examples.pdp.PDPProblem: Returns the number of variables (decisions) in the problem.
nbVars() - Method in class org.ddolib.examples.pigmentscheduling.PSProblem
nbVars() - Method in class org.ddolib.examples.smic.SMICProblem
nbVars() - Method in class org.ddolib.examples.srflp.SRFLPProblem
nbVars() - Method in class org.ddolib.examples.talentscheduling.TSProblem
nbVars() - Method in class org.ddolib.examples.tsp.TSPProblem: Returns the number of decision variables in the problem.
nbVars() - Method in class org.ddolib.examples.tsptw.TSPTWProblem
nbVars() - Method in interface org.ddolib.modeling.Problem
nCities() - Method in class org.ddolib.examples.tsp.TSPGenerator: Returns the number of cities in the instance.
neighbors - Variable in class org.ddolib.examples.misp.MispProblem: For each node i, neighbors[i] contains the adjacency list of i.
netBenefit() - Method in record class org.ddolib.examples.max2sat.Max2SatState: Returns the value of the netBenefit record component.
netBenefit() - Method in record class org.ddolib.examples.mcp.MCPState: Returns the value of the netBenefit record component.
newBest(double) - Method in class org.ddolib.util.verbosity.VerboseMode: Prints message when a new best solution is found.
nextVariable(Set<Integer>, Iterator<T>) - Method in class org.ddolib.ddo.core.heuristics.variable.DefaultVariableHeuristic: Returns the next variable to branch on by selecting the first element from the set of remaining variables.
nextVariable(Set<Integer>, Iterator<T>) - Method in interface org.ddolib.ddo.core.heuristics.variable.VariableHeuristic: Selects the next variable to branch on given the current set of unassigned variables and the states of the next layer.
node - Variable in class org.ddolib.ddo.core.mdd.NodeSubProblem: The actual node from the decision diagram graph.
Node - Class in org.ddolib.ddo.core.mdd: Represents an atomic node in a decision diagram.
Node(double) - Constructor for class org.ddolib.ddo.core.mdd.Node: Creates a new Node with the given value.
NodeSubProblem<T> - Class in org.ddolib.ddo.core.mdd: Encapsulates the association of a node in a decision diagram with its corresponding state and an associated rough lower bound.
NodeSubProblem(T, double, Node) - Constructor for class org.ddolib.ddo.core.mdd.NodeSubProblem: Creates a new NodeSubProblem associating a state with a node and a lower bound.
NodeSubProblemComparator<T> - Class in org.ddolib.ddo.core.mdd: Comparator for NodeSubProblem instances that sorts them first by their node value, and then by the state using a provided StateRanking if the values are equal.
NodeSubProblemComparator(StateRanking<T>) - Constructor for class org.ddolib.ddo.core.mdd.NodeSubProblemComparator: Constructs a new comparator that uses the given ranking as a tie-breaker.
NodeType - Enum Class in org.ddolib.ddo.core.mdd: Enum representing the different types of nodes in the decision diagram.
NORMAL - Enum constant in enum class org.ddolib.util.verbosity.VerbosityLevel: Displays important progress updates.
numEdges - Variable in class org.ddolib.examples.mcp.Graph
numNodes - Variable in class org.ddolib.examples.mcp.Graph

O

objective - Variable in class org.ddolib.examples.tsp.TSPGenerator: Best known objective value (optional, -1 if unknown)
OFF - Enum constant in enum class org.ddolib.util.debug.DebugLevel: Disables all debugging features.
ON - Enum constant in enum class org.ddolib.util.debug.DebugLevel: Enables basic debugging checks.
onLocationActors() - Method in record class org.ddolib.examples.talentscheduling.TSState: Returns the value of the onLocationActors record component.
onLocationActors(BitSet, BitSet) - Method in class org.ddolib.examples.talentscheduling.TSProblem
onLocationActors(TSState) - Method in class org.ddolib.examples.talentscheduling.TSProblem: Returns the set of actors already present on location at the current state, i.e., actors involved in past scenes and needed for future scenes.
optimal - Variable in class org.ddolib.examples.alp.ALPProblem: Known optimal value, if available.
optimal - Variable in class org.ddolib.examples.knapsack.KSProblem: Optional known optimal solution value.
optimal - Variable in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Optional optimal solution value.
optimal - Variable in class org.ddolib.examples.mcp.MCPProblem: Optional known optimal value for the problem instance.
optimal - Variable in class org.ddolib.examples.mks.MKSProblem: Optional known optimal solution value.
optimal - Variable in class org.ddolib.examples.talentscheduling.TSProblem: The optimal solution value if known (optional, used for testing and benchmarking).
optimal - Variable in class org.ddolib.examples.tsptw.TSPTWProblem: Optional known optimal value for the instance.
OPTIMAL - Enum constant in enum class org.ddolib.common.solver.SearchStatus
optimalValue() - Method in class org.ddolib.examples.alp.ALPProblem
optimalValue() - Method in class org.ddolib.examples.gruler.GRProblem: Returns the known optimal value of the problem, if available.
optimalValue() - Method in class org.ddolib.examples.knapsack.KSProblem
optimalValue() - Method in class org.ddolib.examples.lcs.LCSProblem
optimalValue() - Method in class org.ddolib.examples.max2sat.Max2SatProblem
optimalValue() - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns the optimal value of the instance, if known.
optimalValue() - Method in class org.ddolib.examples.mcp.MCPProblem
optimalValue() - Method in class org.ddolib.examples.misp.MispProblem
optimalValue() - Method in class org.ddolib.examples.mks.MKSProblem: Returns the optional optimal value (negated to follow minimization conventions in DDO).
optimalValue() - Method in class org.ddolib.examples.msct.MSCTProblem: Returns the known optimal value of this instance, if available.
optimalValue() - Method in class org.ddolib.examples.pdp.PDPProblem: Returns the known optimal value of the problem, if available.
optimalValue() - Method in class org.ddolib.examples.pigmentscheduling.PSProblem: Returns the known optimal value of the problem, if available.
optimalValue() - Method in class org.ddolib.examples.smic.SMICProblem: Returns the known optimal value of the problem, if available.
optimalValue() - Method in class org.ddolib.examples.srflp.SRFLPProblem
optimalValue() - Method in class org.ddolib.examples.talentscheduling.TSProblem
optimalValue() - Method in class org.ddolib.examples.tsp.TSPProblem: Returns the optimal value of the instance if known.
optimalValue() - Method in class org.ddolib.examples.tsptw.TSPTWProblem
optimalValue() - Method in interface org.ddolib.modeling.Problem: Returns the known optimal value of the problem, if available.
org.ddolib - package org.ddolib: Main package of the framework.
org.ddolib.acs.core - package org.ddolib.acs.core: This package implement Acs search families of search algorithms.
org.ddolib.acs.core.solver - package org.ddolib.acs.core.solver: This package implement Acs solver.
org.ddolib.astar - package org.ddolib.astar: This package implement A-Star search families of search algorithms.
org.ddolib.astar.core.solver - package org.ddolib.astar.core.solver: This package implement As Star solver.
org.ddolib.awastar - package org.ddolib.awastar: This package contains the family of Anytime Weighted A* algorithm
org.ddolib.awastar.core.solver - package org.ddolib.awastar.core.solver: This contains the implementation of a Anytime Weighted A* solver for decision diagram-based optimization problems.
org.ddolib.common - package org.ddolib.common: This package contains the interfaces and classes that can be needed for all kind of solvers
org.ddolib.common.dominance - package org.ddolib.common.dominance: This package contains the classes implementing dominance checkers.
org.ddolib.common.solver - package org.ddolib.common.solver: This package contains interfaces that must be extended to implements solvers.
org.ddolib.ddo - package org.ddolib.ddo: The classes in this package compose the framework you will be using to complete your assignment on the Branch-and-Bound with MDD algorithm.
org.ddolib.ddo.core - package org.ddolib.ddo.core: This package contains the core classes and interfaces that are central to the implementation of an optimization solver based on branch and bound with decision diagrams.
org.ddolib.ddo.core.cache - package org.ddolib.ddo.core.cache: This package contains the implementations of cache mechanism.
org.ddolib.ddo.core.compilation - package org.ddolib.ddo.core.compilation: This package contains defining the compilation type and the compilation input
org.ddolib.ddo.core.frontier - package org.ddolib.ddo.core.frontier: This package contains the classes implementing solver frontiers.
org.ddolib.ddo.core.heuristics - package org.ddolib.ddo.core.heuristics: This package contains the classes and interfaces defining the heuristics which can be used to customize the behavior of an MDD with some default implementations.
org.ddolib.ddo.core.heuristics.cluster - package org.ddolib.ddo.core.heuristics.cluster: This package contains the classes and interfaces defining the heuristics which can be used to discard or merge node during the restriction or relaxation of the MDD.
org.ddolib.ddo.core.heuristics.variable - package org.ddolib.ddo.core.heuristics.variable: This package contains heuristics on variable ordering.
org.ddolib.ddo.core.heuristics.width - package org.ddolib.ddo.core.heuristics.width: This package contains heuristics on the maximum width of a MDD
org.ddolib.ddo.core.mdd - package org.ddolib.ddo.core.mdd: This package contains the classes that are used to implement a restricted/relaxed MDD.
org.ddolib.ddo.core.profiling - package org.ddolib.ddo.core.profiling: This package contains classes useful for the profiling
org.ddolib.ddo.core.solver - package org.ddolib.ddo.core.solver: This package contains solvers using DDO algorithm.
org.ddolib.examples - package org.ddolib.examples: Package containing examples
org.ddolib.examples.alp - package org.ddolib.examples.alp: This package implements the acs, astar and ddo models for the Aircraft Landing Problem (ALP).
org.ddolib.examples.boundedknapsack - package org.ddolib.examples.boundedknapsack: This package implements the acs, astar and ddo models for the Bounded Knapsack Problem (BKS).
org.ddolib.examples.gruler - package org.ddolib.examples.gruler: This package implements the acs, astar and ddo models for the Golomb Rule Problem (GRP).
org.ddolib.examples.knapsack - package org.ddolib.examples.knapsack: This package implements the acs, astar and ddo models for the Knapsack Problem (KS).
org.ddolib.examples.lcs - package org.ddolib.examples.lcs: This package implements the acs, astar and ddo models for the Longest Common Subsequence (LCS) Problem.
org.ddolib.examples.max2sat - package org.ddolib.examples.max2sat: This package implements the acs, astar and ddo models for the Maximum 2-Satisfiability Problem (MAX2SAT) Problem.
org.ddolib.examples.maximumcoverage - package org.ddolib.examples.maximumcoverage
org.ddolib.examples.mcp - package org.ddolib.examples.mcp: This package implements the acs, astar and ddo models for the Maximum Cut Problem (MCP).
org.ddolib.examples.misp - package org.ddolib.examples.misp: This package implements the acs, astar and ddo models for the Maximum Independent Set Problem (MISP).
org.ddolib.examples.mks - package org.ddolib.examples.mks: The Multidimensional Knapsack Problem (MKP) is a generalization of the KP to multiple capacity constraints: $n$ items and $m$ dimensions of the knapsack are given, each dimension with capacity bound $(C_1,\ldots ,C_m)$.
org.ddolib.examples.msct - package org.ddolib.examples.msct: This package implements the acs, astar and ddo models for the Minimum Sum Completion Time (MSCT).
org.ddolib.examples.pdp - package org.ddolib.examples.pdp: This package implements the acs, astar and ddo models for the Single Vehicle Pick-up and Delivery Problem (PDP).
org.ddolib.examples.pigmentscheduling - package org.ddolib.examples.pigmentscheduling: This package implements the acs, astar and ddo models for the Pigment Sequencing Problem (PSP).
org.ddolib.examples.smic - package org.ddolib.examples.smic: This package implements the acs, astar and ddo models for the Single Machine with Inventory Constraint (SMIC).
org.ddolib.examples.srflp - package org.ddolib.examples.srflp: This package implements the acs, astar and ddo models for the Single Row Facility Layout Problem (SRFLP).
org.ddolib.examples.talentscheduling - package org.ddolib.examples.talentscheduling: This package implements the acs, astar and ddo models for the Talent Scheduling problem (talentSched).
org.ddolib.examples.tsp - package org.ddolib.examples.tsp: This package implements the acs, astar and ddo models for the Traveling Salesman Problem (TSP).
org.ddolib.examples.tsptw - package org.ddolib.examples.tsptw: This package implements the acs, astar and ddo models for the Traveling Salesman Problem with Time Window (TSPTW).
org.ddolib.lns.core.solver - package org.ddolib.lns.core.solver: This package implement LNS solver.
org.ddolib.modeling - package org.ddolib.modeling: This package contains the interfaces and abstract classes that must be implemented as problem specific classes to model a problem.It also contains default implementation.
org.ddolib.util - package org.ddolib.util: This package contains the classes implementing utils user in the solver
org.ddolib.util.debug - package org.ddolib.util.debug: This package contains util stuff related to the debug mode.
org.ddolib.util.io - package org.ddolib.util.io: Input file reader utility
org.ddolib.util.verbosity - package org.ddolib.util.verbosity: This package contains util stuff related the verbose mode.
origin - Variable in class org.ddolib.ddo.core.mdd.Edge: The source node of this edge.
Output - Search tag in class org.ddolib.examples.alp.ALPLnsMain: Section
Output - Search tag in class org.ddolib.examples.boundedknapsack.BKSLnsMain: Section
Output - Search tag in class org.ddolib.examples.knapsack.KSLnsMain: Section
Output - Search tag in class org.ddolib.examples.lcs.LCSLnsMain: Section
Output - Search tag in class org.ddolib.examples.max2sat.Max2SatLnsMain: Section
Output - Search tag in class org.ddolib.examples.maximumcoverage.MaxCoverLnsMain: Section
Output - Search tag in class org.ddolib.examples.mcp.MCPLnsMain: Section
Output - Search tag in class org.ddolib.examples.misp.MispLnsMain: Section
Output - Search tag in class org.ddolib.examples.msct.MSCTLnsMain: Section
Output - Search tag in class org.ddolib.examples.pdp.PDPLnsMain: Section
Output - Search tag in class org.ddolib.examples.pigmentscheduling.PSLnsMain: Section

P

p() - Method in record class org.ddolib.examples.tsptw.TSPTWDominanceKey: Returns the value of the p record component.
PDPAcsMain - Class in org.ddolib.examples.pdp: Single Vehicle Pick-up and Delivery Problem (PDP) with Acs.
PDPAcsMain() - Constructor for class org.ddolib.examples.pdp.PDPAcsMain
PDPAstarMain - Class in org.ddolib.examples.pdp: Single Vehicle Pick-up and Delivery Problem (PDP) with AsTar.
PDPAstarMain() - Constructor for class org.ddolib.examples.pdp.PDPAstarMain
PDPDdoMain - Class in org.ddolib.examples.pdp: Single Vehicle Pick-up and Delivery Problem (PDP) with Ddo.
PDPDdoMain() - Constructor for class org.ddolib.examples.pdp.PDPDdoMain
PDPFastLowerBound - Class in org.ddolib.examples.pdp: Provides a fast lower bound estimation for the Pickup and Delivery Problem (PDP).
PDPFastLowerBound(PDPProblem) - Constructor for class org.ddolib.examples.pdp.PDPFastLowerBound: Constructs a new fast lower bound estimator for a given PDP problem instance.
PDPGenerator - Class in org.ddolib.examples.pdp: Utility class for generating instances of the Pickup and Delivery Problem (PDP) with a single vehicle.
PDPGenerator() - Constructor for class org.ddolib.examples.pdp.PDPGenerator
PDPLnsMain - Class in org.ddolib.examples.pdp: Entry point for solving the Single Vehicle Pick-up and Delivery Problem (PDP) using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
PDPLnsMain() - Constructor for class org.ddolib.examples.pdp.PDPLnsMain
PDPProblem - Class in org.ddolib.examples.pdp: Represents a Pickup and Delivery Problem (PDP) instance with a single vehicle.
PDPProblem(double[][], HashMap<Integer, Integer>, int) - Constructor for class org.ddolib.examples.pdp.PDPProblem: Constructs a PDPProblem from a distance matrix, a map of pickup-delivery pairs, and a maximum vehicle capacity.
PDPProblem(String) - Constructor for class org.ddolib.examples.pdp.PDPProblem: Constructs a PDPProblem by reading an instance from a file.
PDPRanking - Class in org.ddolib.examples.pdp: Implements a state ranking strategy for the Pickup and Delivery Problem (PDP).
PDPRanking() - Constructor for class org.ddolib.examples.pdp.PDPRanking
PDPSolution - Class in org.ddolib.examples.pdp: Represents a solution to a Pickup and Delivery Problem (PDP) instance.
PDPSolution(PDPProblem, int[], double) - Constructor for class org.ddolib.examples.pdp.PDPSolution: Constructs a PDP solution with the given problem, solution sequence, and value.
PDPState - Class in org.ddolib.examples.pdp: Represents the state of a Pickup and Delivery Problem (PDP) during the search process.
PDPState(BitSet, BitSet, BitSet, int, int) - Constructor for class org.ddolib.examples.pdp.PDPState: Constructs a PDPState.
pickupToAssociatedDelivery - Variable in class org.ddolib.examples.pdp.PDPProblem: Map of pickup nodes to their associated delivery nodes.
pop() - Method in interface org.ddolib.ddo.core.frontier.Frontier: Extracts and returns the most promising subproblem from the frontier.
pop() - Method in class org.ddolib.ddo.core.frontier.SimpleFrontier: Removes and returns the most promising subproblem from the frontier.
position() - Method in record class org.ddolib.examples.tsptw.TSPTWState: Returns the value of the position record component.
possiblyVisit() - Method in record class org.ddolib.examples.tsptw.TSPTWState: Returns the value of the possiblyVisit record component.
PrettyPrint - Class in org.ddolib.util: Collection of utility functions for formatting data for display.
PrettyPrint() - Constructor for class org.ddolib.util.PrettyPrint
prevClass - Variable in class org.ddolib.examples.alp.RunwayState
prevTime - Variable in class org.ddolib.examples.alp.RunwayState
printSolution(SearchStatistics, int[]) - Static method in class org.ddolib.util.io.SolutionPrinter: Prints a newly found solution and its associated statistics to the standard output.
probability - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Probability parameter used in randomized strategies (e.g., LNS or heuristics).
probability() - Method in interface org.ddolib.modeling.LnsModel: Returns the probability used to destruct parts of the solution in LNS.
problem - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Reference to the optimization or constraint problem being solved.
problem() - Method in interface org.ddolib.modeling.Model: Returns the optimization problem instance associated with this model.
Problem<T> - Interface in org.ddolib.modeling: Represents an optimization problem formulated as a labeled transition system, following the semantics of dynamic programming.
profit - Variable in class org.ddolib.examples.knapsack.KSProblem: Profits of the items.
PSAcsMain - Class in org.ddolib.examples.pigmentscheduling: The Pigment Sequencing Problem (PSP) with Acs.
PSAcsMain() - Constructor for class org.ddolib.examples.pigmentscheduling.PSAcsMain
PSAstarMain - Class in org.ddolib.examples.pigmentscheduling: The Pigment Sequencing Problem (PSP) with AsTar.
PSAstarMain() - Constructor for class org.ddolib.examples.pigmentscheduling.PSAstarMain
PSDdoMain - Class in org.ddolib.examples.pigmentscheduling: The Pigment Sequencing Problem (PSP) with Ddo.
PSDdoMain() - Constructor for class org.ddolib.examples.pigmentscheduling.PSDdoMain
PSFastLowerBound - Class in org.ddolib.examples.pigmentscheduling: Computes a fast lower bound for the Pigment Sequencing Problem (PSP).
PSFastLowerBound(PSProblem) - Constructor for class org.ddolib.examples.pigmentscheduling.PSFastLowerBound: Constructs a fast lower bound evaluator for a given PSP instance.
PSLnsMain - Class in org.ddolib.examples.pigmentscheduling: Entry point for solving the Pigment Sequencing Problem (PSP) using a Large Neighborhood Search (LNS) approach combined with Decision Diagram Optimization (DDO).
PSLnsMain() - Constructor for class org.ddolib.examples.pigmentscheduling.PSLnsMain
PSProblem - Class in org.ddolib.examples.pigmentscheduling: Represents an instance of the Pigment Sequencing Problem (PSP) used within a Decision Diagram Optimization (DDO) framework.
PSProblem(int, int, int[], int[][], int[][]) - Constructor for class org.ddolib.examples.pigmentscheduling.PSProblem: Constructs a PSP instance from explicit data arrays without a known optimal value.
PSProblem(int, int, int[], int[][], int[][], Optional<Double>) - Constructor for class org.ddolib.examples.pigmentscheduling.PSProblem: Constructs a PSP instance from explicit data arrays and a known optimal value.
PSProblem(String) - Constructor for class org.ddolib.examples.pigmentscheduling.PSProblem: Constructs a PSP instance from a data file.
PSRanking - Class in org.ddolib.examples.pigmentscheduling: Provides a ranking heuristic for comparing two PSState objects within the Production Scheduling Problem (PSP) search framework.
PSRanking() - Constructor for class org.ddolib.examples.pigmentscheduling.PSRanking
PSRelax - Class in org.ddolib.examples.pigmentscheduling: Implements the relaxation mechanism used in the DDO framework for the Pigment Scheduling Problem (PSP).
PSRelax(PSProblem) - Constructor for class org.ddolib.examples.pigmentscheduling.PSRelax: Constructs a relaxation operator associated with a given PSP problem.
PSState - Class in org.ddolib.examples.pigmentscheduling: Represents a state in the Production Scheduling Problem (PSP).
PSState(int, int, int[]) - Constructor for class org.ddolib.examples.pigmentscheduling.PSState: Constructs a new state for the PSP.
push(SubProblem<T>) - Method in interface org.ddolib.ddo.core.frontier.Frontier: Adds a new subproblem to the frontier for future exploration.
push(SubProblem<T>) - Method in class org.ddolib.ddo.core.frontier.SimpleFrontier: Adds a subproblem to the frontier.

Q

quantities - Variable in class org.ddolib.examples.boundedknapsack.BKSProblem
queueMaxSize() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns the value of the queueMaxSize record component.

R

RandomBased<T> - Class in org.ddolib.ddo.core.heuristics.cluster: A simple random-based reduction strategy for decision diagram layers.
RandomBased(long) - Constructor for class org.ddolib.ddo.core.heuristics.cluster.RandomBased: Constructs a random-based reduction strategy with a given seed.
rank(Max2SatState) - Static method in class org.ddolib.examples.max2sat.Max2SatRanking
rank(MCPState) - Static method in class org.ddolib.examples.mcp.MCPRanking
ranking() - Method in interface org.ddolib.modeling.DdoModel: Returns the ranking function used to order states within a layer.
ranking() - Method in class org.ddolib.modeling.ExactModel
ranking() - Method in interface org.ddolib.modeling.LnsModel: Returns the state ranking heuristic used to guide the search.
reductionStrategy - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Strategy used to reduce the width of the MDD by merging or discarding nodes.
ReductionStrategy<T> - Interface in org.ddolib.ddo.core.heuristics.cluster: Interface defining a strategy to reduce the number of nodes in a layer of a decision diagram by clustering nodes for restriction and relaxation.
relaxation - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Relaxation model used to approximate or merge states in relaxed MDD compilation.
relaxation() - Method in interface org.ddolib.modeling.DdoModel: Returns the relaxation of the model used to evaluate the nodes or layers of the decision diagram.
relaxation() - Method in class org.ddolib.modeling.ExactModel
Relaxation<T> - Interface in org.ddolib.modeling: This is the second most important abstraction that a client should provide when using this library.
RelaxationSolver<T> - Class in org.ddolib.ddo.core.solver: A solver that compile one relaxed MDD from the root node.
RelaxationSolver(DdoModel<T>) - Constructor for class org.ddolib.ddo.core.solver.RelaxationSolver: Creates a fully qualified instance.
Relaxed - Enum constant in enum class org.ddolib.ddo.core.compilation.CompilationType: Compile a relaxed decision diagram.
RELAXED - Enum constant in enum class org.ddolib.ddo.core.mdd.NodeType: Represents a relaxed node in the decision diagram.
relaxedBestPathIsExact() - Method in interface org.ddolib.ddo.core.mdd.DecisionDiagram: Checks whether the best path found in the relaxed decision diagram is exact.
relaxedBestPathIsExact() - Method in class org.ddolib.ddo.core.mdd.LinkedDecisionDiagram: Checks whether the best path found in a relaxed MDD consists entirely of exact nodes.
relaxedDdo(DdoModel<T>) - Static method in class org.ddolib.modeling.Solvers
relaxedDdo(DdoModel<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers
relaxedDdo(DdoModel<T>, Predicate<SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers
relaxedDdo(DdoModel<T>, Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers
relaxEdge(Integer, Integer, Integer, Decision, double) - Method in class org.ddolib.examples.boundedknapsack.BKSRelax: Optionally relaxes the edge cost when transitioning from a state to a merged state.
relaxEdge(Integer, Integer, Integer, Decision, double) - Method in class org.ddolib.examples.knapsack.KSRelax: Relaxes the cost of an edge between states in the decision diagram.
relaxEdge(BitSet, BitSet, BitSet, Decision, double) - Method in class org.ddolib.examples.misp.MispRelax: Adjusts the transition cost when moving from one state to another in the relaxed space.
relaxEdge(ALPState, ALPState, ALPState, Decision, double) - Method in class org.ddolib.examples.alp.ALPRelax: Returns the relaxed cost of a transition (edge) between states.
relaxEdge(GRState, GRState, GRState, Decision, double) - Method in class org.ddolib.examples.gruler.GRRelax: Computes the relaxed cost of transitioning between two states in the relaxed problem.
relaxEdge(LCSState, LCSState, LCSState, Decision, double) - Method in class org.ddolib.examples.lcs.LCSRelax: Relaxes the cost of a transition between two LCS states.
relaxEdge(Max2SatState, Max2SatState, Max2SatState, Decision, double) - Method in class org.ddolib.examples.max2sat.Max2SatRelax: Adjusts the cost of transitioning from one state to another in the relaxed model.
relaxEdge(MaxCoverState, MaxCoverState, MaxCoverState, Decision, double) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverRelax: Computes the relaxed cost of a transition between states.
relaxEdge(MCPState, MCPState, MCPState, Decision, double) - Method in class org.ddolib.examples.mcp.MCPRelax: Computes the relaxed transition cost from one state to another given a merged state.
relaxEdge(MKSState, MKSState, MKSState, Decision, double) - Method in class org.ddolib.examples.mks.MKSRelax: Returns the cost of an edge in the relaxed decision diagram.
relaxEdge(MSCTState, MSCTState, MSCTState, Decision, double) - Method in class org.ddolib.examples.msct.MSCTRelax: Computes the relaxed cost associated with transitioning from one state to another.
relaxEdge(PSState, PSState, PSState, Decision, double) - Method in class org.ddolib.examples.pigmentscheduling.PSRelax: Returns the relaxed transition cost between two PSP states.
relaxEdge(SMICState, SMICState, SMICState, Decision, double) - Method in class org.ddolib.examples.smic.SMICRelax: Relaxes the cost of an edge between two states.
relaxEdge(SRFLPState, SRFLPState, SRFLPState, Decision, double) - Method in class org.ddolib.examples.srflp.SRFLPRelax: Relaxation of an edge cost between two states.
relaxEdge(TSState, TSState, TSState, Decision, double) - Method in class org.ddolib.examples.talentscheduling.TSRelax: Returns the relaxed edge cost between two states.
relaxEdge(TSPState, TSPState, TSPState, Decision, double) - Method in class org.ddolib.examples.tsp.TSPRelax: Relaxes the cost of a transition between states.
relaxEdge(TSPTWState, TSPTWState, TSPTWState, Decision, double) - Method in class org.ddolib.examples.tsptw.TSPTWRelax: Relaxes the cost of an edge (transition) between two states.
relaxEdge(T, T, T, Decision, double) - Method in interface org.ddolib.modeling.Relaxation: Relaxes the edge that used to go from `from` to `to` and computes the cost of the new edge going from `from` to `merged`.
relaxStrategy() - Method in interface org.ddolib.modeling.DdoModel: Strategy to select which nodes should be merged together on a relaxed DD.
relaxStrategy() - Method in class org.ddolib.modeling.ExactModel
remainingAircraftOfClass - Variable in class org.ddolib.examples.alp.ALPState: Number of remaining aircraft for each class.
remainingJobs() - Method in record class org.ddolib.examples.msct.MSCTState: Returns the value of the remainingJobs record component.
remainingJobs() - Method in record class org.ddolib.examples.smic.SMICState: Returns the value of the remainingJobs record component.
remainingNodes - Variable in class org.ddolib.examples.misp.MispProblem: The remaining nodes that can be selected in the current independent set.
remainingScenes() - Method in record class org.ddolib.examples.talentscheduling.TSState: Returns the value of the remainingScenes record component.
residual - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: The residual (sub)problem defining the remaining search space to explore during compilation.
Responsibilities - Search tag in interface org.ddolib.modeling.DdoModel: Section
Restricted - Enum constant in enum class org.ddolib.ddo.core.compilation.CompilationType: Compile a restricted decision diagram.
restrictedDdo(DdoModel<T>) - Static method in class org.ddolib.modeling.Solvers
restrictedDdo(DdoModel<T>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers
restrictedDdo(DdoModel<T>, Predicate<SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers
restrictedDdo(DdoModel<T>, Predicate<SearchStatistics>, BiConsumer<int[], SearchStatistics>) - Static method in class org.ddolib.modeling.Solvers
RestrictionSolver<T> - Class in org.ddolib.ddo.core.solver: A solver that compile one relaxed MDD from the root node.
RestrictionSolver(DdoModel<T>) - Constructor for class org.ddolib.ddo.core.solver.RestrictionSolver: Creates a fully qualified instance.
restrictStrategy() - Method in interface org.ddolib.modeling.DdoModel: Strategy to select which nodes should be dropped on a restricted DD.
restrictStrategy() - Method in class org.ddolib.modeling.ExactModel
restrictStrategy() - Method in interface org.ddolib.modeling.LnsModel: Returns the strategy used to restrict the search neighborhood.
runTimeMs() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns the value of the runTimeMs record component.
runway - Variable in class org.ddolib.examples.alp.ALPDecision: The runway to which the aircraft is assigned.
RunwayState - Class in org.ddolib.examples.alp: State of a runway : last landing time and last aircraft's class
RunwayState(int, int) - Constructor for class org.ddolib.examples.alp.RunwayState
RunwayState(RunwayState) - Constructor for class org.ddolib.examples.alp.RunwayState
runwayStates - Variable in class org.ddolib.examples.alp.ALPState: State of each runway, including last landed aircraft class and landing time.

S

S - Variable in class org.ddolib.examples.mcp.MCPProblem: Constant to model decision "put in partition S".
SAT - Enum constant in enum class org.ddolib.common.solver.SearchStatus
saturatedAdd(double, double) - Static method in class org.ddolib.util.MathUtil: Performs a saturated addition of two double values.
saturatedDiff(double, double) - Static method in class org.ddolib.util.MathUtil: Performs a saturated subtraction of two double values.
saveXml(String, int) - Method in class org.ddolib.examples.tsp.TSPGenerator: Saves the TSP instance in XML format following XML-TSPLIB standards.
sceneCost(int) - Method in class org.ddolib.examples.talentscheduling.TSProblem
Search Configuration - Search tag in class org.ddolib.examples.alp.ALPLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.boundedknapsack.BKSLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.knapsack.KSLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.lcs.LCSLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.max2sat.Max2SatLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.maximumcoverage.MaxCoverLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.mcp.MCPLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.misp.MispLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.msct.MSCTLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.pdp.PDPLnsMain: Section
Search Configuration - Search tag in class org.ddolib.examples.pigmentscheduling.PSLnsMain: Section
SearchStatistics - Record Class in org.ddolib.common.solver
SearchStatistics(SearchStatus, int, int, long, double, double) - Constructor for record class org.ddolib.common.solver.SearchStatistics: Creates an instance of a SearchStatistics record class.
SearchStatus - Enum Class in org.ddolib.common.solver
searchTime() - Method in class org.ddolib.common.solver.Solution
SequentialSolver<T> - Class in org.ddolib.ddo.core.solver: A sequential implementation of a Branch-and-Bound solver based on Multi-valued Decision Diagrams (MDDs).
SequentialSolver(DdoModel<T>) - Constructor for class org.ddolib.ddo.core.solver.SequentialSolver: Creates a fully qualified instance.
setColumnWidth(int) - Method in interface org.ddolib.modeling.AcsModel: Returns a copy of this model but with another column width.
setCutSetType(CutSetType) - Method in interface org.ddolib.modeling.DdoModel: Returns a copy of this model by changing the CutSetType.
setExplored(boolean) - Method in class org.ddolib.ddo.core.cache.Threshold: Sets the exploration status of the state.
setInitialSolution(int[]) - Method in interface org.ddolib.modeling.LnsModel: Returns a copy of this model with a specified initial solution.
setName(String) - Method in class org.ddolib.examples.pigmentscheduling.PSProblem: Assigns a name to the problem instance for display or debugging purposes.
setProbability(double) - Method in interface org.ddolib.modeling.LnsModel: Returns a copy of this model with a specified destruction probability.
setSeed(long) - Method in class org.ddolib.ddo.core.heuristics.cluster.GHP: Sets the seed of the internal random number generator.
setSeed(long) - Method in class org.ddolib.ddo.core.heuristics.cluster.Hybrid: Sets the random seed used for the distance-based GHP clustering.
setSeed(long) - Method in class org.ddolib.ddo.core.heuristics.cluster.RandomBased: Resets the seed of the random number generator.
setValue(double) - Method in class org.ddolib.ddo.core.cache.Threshold: Sets the numeric value of this threshold.
setWeight(double) - Method in interface org.ddolib.modeling.AwAstarModel: Returns a copy of this model but with another weight.
shuffle(int[]) - Static method in class org.ddolib.util.ArraysUtil: Randomly shuffles the elements of the given integer array in place.
SILENT - Enum constant in enum class org.ddolib.util.verbosity.VerbosityLevel: No output is produced.
SimpleCache<T> - Class in org.ddolib.ddo.core.cache: A simple implementation of a Cache for storing threshold values associated with states in a dynamic programming model.
SimpleCache() - Constructor for class org.ddolib.ddo.core.cache.SimpleCache: Constructs an empty SimpleCache.
SimpleCache.Layer<T> - Class in org.ddolib.ddo.core.cache: Inner class representing a synchronized cache layer for a specific depth.
SimpleDominanceChecker<T> - Class in org.ddolib.common.dominance: The SimpleDominanceChecker class implements a straightforward dominance management mechanism used in search algorithms based on Multi-valued Decision Diagrams (MDDs), such as DDO (Decision Diagram Optimization).
SimpleDominanceChecker(Dominance<T>, int) - Constructor for class org.ddolib.common.dominance.SimpleDominanceChecker: Constructs a SimpleDominanceChecker with the given dominance relation and number of decision variables.
SimpleFrontier<T> - Class in org.ddolib.ddo.core.frontier: A simple implementation of a Frontier for a solver, based on a plain priority queue.
SimpleFrontier(StateRanking<T>, CutSetType) - Constructor for class org.ddolib.ddo.core.frontier.SimpleFrontier: Constructs a new SimpleFrontier.
singleton(int) - Method in class org.ddolib.examples.pdp.PDPProblem
singleton(int) - Method in class org.ddolib.examples.pdp.PDPState: Returns a BitSet containing a single value.
singleton(int) - Method in class org.ddolib.examples.tsp.TSPProblem: Creates a BitSet containing only a single node.
singleton(int) - Method in class org.ddolib.examples.tsp.TSPState: Creates a BitSet containing only the specified singleton value.
size() - Method in interface org.ddolib.ddo.core.frontier.Frontier: Returns the number of subproblems currently stored in the frontier.
size() - Method in class org.ddolib.ddo.core.frontier.SimpleFrontier: Returns the number of subproblems currently in the frontier.
skipLine() - Method in class org.ddolib.util.io.InputReader: Skips the next line in the input.
SMICAcsMain - Class in org.ddolib.examples.smic: The Single Machine with Inventory Constraint (SMIC) with Acs.
SMICAcsMain() - Constructor for class org.ddolib.examples.smic.SMICAcsMain
SMICAstarMain - Class in org.ddolib.examples.smic: The Single Machine with Inventory Constraint (SMIC) with AsTar.
SMICAstarMain() - Constructor for class org.ddolib.examples.smic.SMICAstarMain
SMICDdoMain - Class in org.ddolib.examples.smic: The Single Machine with Inventory Constraint (SMIC) with Ddo.
SMICDdoMain() - Constructor for class org.ddolib.examples.smic.SMICDdoMain
SMICDominance - Class in org.ddolib.examples.smic: The SMICDominance class defines the dominance relation between two states of the SMICState in the context of the Single Machine with Inventory Constraint (SMIC) problem.
SMICDominance() - Constructor for class org.ddolib.examples.smic.SMICDominance
SMICFastLowerBound - Class in org.ddolib.examples.smic: The SMICFastLowerBound class provides a fast and simple estimation of the lower bound of the remaining cost (or completion time) in the Single Machine with Inventory Constraint (SMIC) scheduling problem.
SMICFastLowerBound(SMICProblem) - Constructor for class org.ddolib.examples.smic.SMICFastLowerBound: Constructs a fast lower bound estimator for the given SMIC problem.
SMICGenrator - Class in org.ddolib.examples.smic: The SMICGenrator class is responsible for generating random instances of the Single Machine with Inventory Constraint (SMIC) problem.
SMICGenrator(int, int, double, int, long) - Constructor for class org.ddolib.examples.smic.SMICGenrator: Constructs a new SMIC instance generator with the given parameters.
SMICLnsMain - Class in org.ddolib.examples.smic: Entry point for solving the Single Machine with Inventory Constraint (SMIC) problem using a Large Neighborhood Search (LNS) approach.
SMICLnsMain() - Constructor for class org.ddolib.examples.smic.SMICLnsMain
SMICProblem - Class in org.ddolib.examples.smic: The SMICProblem class represents an instance of the Single Machine with Inventory Constraint (SMIC) scheduling problem.
SMICProblem(String) - Constructor for class org.ddolib.examples.smic.SMICProblem: Constructs a SMICProblem instance by parsing a text file.
SMICProblem(String, int, int, int, int[], int[], int[], int[], int[]) - Constructor for class org.ddolib.examples.smic.SMICProblem: Constructs a SMICProblem instance without a known optimal value.
SMICProblem(String, int, int, int, int[], int[], int[], int[], int[], Optional<Double>) - Constructor for class org.ddolib.examples.smic.SMICProblem: Constructs a SMICProblem instance with full specification.
SMICRanking - Class in org.ddolib.examples.smic: The SMICRanking class defines a heuristic ranking criterion for comparing two SMICState instances during search or optimization.
SMICRanking() - Constructor for class org.ddolib.examples.smic.SMICRanking
SMICRelax - Class in org.ddolib.examples.smic: The SMICRelax class implements a relaxation operator for the SMICProblem, used in Decision Diagram Optimization (DDO)-based solvers.
SMICRelax(SMICProblem) - Constructor for class org.ddolib.examples.smic.SMICRelax: Constructs a relaxation operator for the given SMICProblem.
SMICState - Record Class in org.ddolib.examples.smic: The SMICState record represents a state in the search space of the Single Machine with Inventory Constraint (SMIC) scheduling problem.
SMICState(BitSet, int, int, int) - Constructor for record class org.ddolib.examples.smic.SMICState: Creates an instance of a SMICState record class.
solution - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Stores the current or best solution found during compilation.
solution - Variable in class org.ddolib.examples.pdp.PDPSolution: The sequence of nodes representing the solution, including pickups, deliveries, and unrelated nodes.
solution() - Method in class org.ddolib.common.solver.Solution: Returns an array t such that t[i] is the assigned value to the decision variable x_i.
Solution - Class in org.ddolib.common.solver: Wrapper defining a solution from a set of decisions
Solution(Optional<Set<Decision>>, SearchStatistics) - Constructor for class org.ddolib.common.solver.Solution: Constructs a solution given a set of decision and SearchStatistics on this set.
SolutionPrinter - Class in org.ddolib.util.io: Utility class providing helper methods to display solutions found by a solver.
SolutionPrinter() - Constructor for class org.ddolib.util.io.SolutionPrinter
Solver - Interface in org.ddolib.common.solver: Interface representing a generic solver for decision diagram based optimization problems.
Solvers - Class in org.ddolib.modeling: The Solvers class acts as a unified entry point for running different optimization algorithms within the Decision Diagram Optimization (DDO) framework.
Solvers() - Constructor for class org.ddolib.modeling.Solvers
SolverUtil - Class in org.ddolib.util: Contains method useful to implements solvers
SolverUtil() - Constructor for class org.ddolib.util.SolverUtil
SRFLPAcsMain - Class in org.ddolib.examples.srflp: The Single-Row Facility Layout Problem (SRFLP) with Acs.
SRFLPAcsMain() - Constructor for class org.ddolib.examples.srflp.SRFLPAcsMain
SRFLPAstarMain - Class in org.ddolib.examples.srflp: The Single-Row Facility Layout Problem (SRFLP) with AsTar.
SRFLPAstarMain() - Constructor for class org.ddolib.examples.srflp.SRFLPAstarMain
SRFLPDdoMain - Class in org.ddolib.examples.srflp: The Single-Row Facility Layout Problem (SRFLP) with Ddo.
SRFLPDdoMain() - Constructor for class org.ddolib.examples.srflp.SRFLPDdoMain
SRFLPFastLowerBound - Class in org.ddolib.examples.srflp: Provides a fast lower-bound estimation for the Single-Row Facility Layout Problem (SRFLP) based on the current state of the solution.
SRFLPFastLowerBound(SRFLPProblem) - Constructor for class org.ddolib.examples.srflp.SRFLPFastLowerBound: Constructs a fast lower-bound estimator for the given SRFLP problem.
SRFLPLnsMain - Class in org.ddolib.examples.srflp: Entry point for solving the Single Row Facility Layout Problem (SRFLP) using a Large Neighborhood Search (LNS) approach.
SRFLPLnsMain() - Constructor for class org.ddolib.examples.srflp.SRFLPLnsMain
SRFLPProblem - Class in org.ddolib.examples.srflp: A Single-Row Facility Layout Problem (SRFLP) instance.
SRFLPProblem(int[], int[][]) - Constructor for class org.ddolib.examples.srflp.SRFLPProblem: Constructs a new SRFLP instance with given lengths and flows.
SRFLPProblem(int[], int[][], Optional<Double>) - Constructor for class org.ddolib.examples.srflp.SRFLPProblem: Constructs a new SRFLP instance with given lengths, flows, and optional known optimal.
SRFLPProblem(String) - Constructor for class org.ddolib.examples.srflp.SRFLPProblem: Reads an SRFLP instance from a file.
SRFLPRanking - Class in org.ddolib.examples.srflp: Implements a ranking between two SRFLPState instances for use in decision diagram or search-based algorithms.
SRFLPRanking() - Constructor for class org.ddolib.examples.srflp.SRFLPRanking
SRFLPRelax - Class in org.ddolib.examples.srflp: Implementation of a relaxation for the Single Row Facility Layout Problem (SRFLP).
SRFLPRelax(SRFLPProblem) - Constructor for class org.ddolib.examples.srflp.SRFLPRelax: Constructs a new relaxation instance for a given SRFLP problem.
SRFLPState - Record Class in org.ddolib.examples.srflp: Represents a state in a Single Row Facility Layout Problem (SRFLP) instance.
SRFLPState(BitSet, BitSet, int[], int) - Constructor for record class org.ddolib.examples.srflp.SRFLPState: Creates an instance of a SRFLPState record class.
start() - Method in record class org.ddolib.examples.tsptw.TimeWindow: Returns the value of the start record component.
state - Variable in class org.ddolib.ddo.core.mdd.NodeSubProblem: The state associated with this node.
state() - Method in record class org.ddolib.util.StateAndDepth: Returns the value of the state record component.
StateAndDepth<T> - Record Class in org.ddolib.util: Class containing a state and its depth in the main search.
StateAndDepth(T, int) - Constructor for record class org.ddolib.util.StateAndDepth: Creates an instance of a StateAndDepth record class.
stateDistance() - Method in interface org.ddolib.modeling.DdoModel
stateDistance() - Method in class org.ddolib.modeling.ExactModel
stateDistance() - Method in interface org.ddolib.modeling.LnsModel: Returns a measure of distance between two states.
StateDistance<T> - Interface in org.ddolib.ddo.core.heuristics.cluster: Interface defining a distance function between states, used to form clusters when deciding which nodes on a layer of a decision diagram should be merged.
stateRanking - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Ranking heuristic used to prioritize states when pruning nodes in width-limited MDD layers.
StateRanking<T> - Interface in org.ddolib.modeling: A state ranking is used to order the states and decides the ones that are kept and the ones that are merged/deleted when a relaxation/restriction occurs.
statistics() - Method in class org.ddolib.common.solver.Solution: Returns the statistics associated to this solution.
statistics() - Method in class org.ddolib.ddo.core.SubProblem: Returns a string summarizing key statistics about this subproblem, including its objective value, lower bound, and depth in the decision diagram.
stats() - Method in class org.ddolib.ddo.core.cache.SimpleCache: Returns statistics about the cache, including number of hits, tests, and total entries.
status() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns the value of the status record component.
STRONGLY_CORRELATED - Enum constant in enum class org.ddolib.examples.boundedknapsack.BKSProblem.InstanceType
SubProblem<T> - Class in org.ddolib.ddo.core: Represents a residual optimization problem (subproblem) derived from the decomposition of an original problem during the compilation or search process.
SubProblem(T, double, double, Set<Decision>) - Constructor for class org.ddolib.ddo.core.SubProblem: Constructs a new SubProblem instance with its associated state, accumulated value, lower bound, and decision path.
SUBSET_SUM - Enum constant in enum class org.ddolib.examples.boundedknapsack.BKSProblem.InstanceType
subSets - Variable in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Array of subsets represented as BitSets, where each BitSet indicates the items it covers.
suffix - Variable in class org.ddolib.ddo.core.mdd.Node: The length of the longest suffix of this node (used in local bound calculations).
symmetricDifferenceDistance(BitSet, BitSet) - Static method in class org.ddolib.util.DistanceUtil: Computes the size of the symmetric difference between a and b

T

t(int) - Method in class org.ddolib.examples.max2sat.Max2SatProblem: Returns the positive literal for a variable.
T - Variable in class org.ddolib.examples.mcp.MCPProblem: Constant to model decision "put in partition T".
Threshold - Class in org.ddolib.ddo.core.cache: Represents a threshold value associated with a state in a dynamic programming or search model.
Threshold(int, boolean) - Constructor for class org.ddolib.ddo.core.cache.Threshold: Constructs a new threshold with a given value and exploration status.
time() - Method in record class org.ddolib.examples.tsptw.TSPTWState: Returns the value of the time record component.
TimeWindow - Record Class in org.ddolib.examples.tsptw: Represents a time window with a start and end time.
TimeWindow(int, int) - Constructor for record class org.ddolib.examples.tsptw.TimeWindow: Creates an instance of a TimeWindow record class.
timeWindows - Variable in class org.ddolib.examples.tsptw.TSPTWProblem: Time windows for each node.
toCSV() - Method in record class org.ddolib.common.solver.SearchStatistics
toDecision(ALPDecision) - Method in class org.ddolib.examples.alp.ALPProblem: Converts an ALPDecision to its integer representation.
toExactModel() - Method in interface org.ddolib.modeling.DdoModel: Convert this model into a model for the exact solver.
toString() - Method in record class org.ddolib.common.solver.SearchStatistics: Returns a string representation of this record class.
toString() - Method in class org.ddolib.common.solver.Solution
toString() - Method in class org.ddolib.ddo.core.cache.SimpleCache.Layer
toString() - Method in class org.ddolib.ddo.core.cache.Threshold: Returns a string representation of this threshold.
toString() - Method in class org.ddolib.ddo.core.compilation.CompilationConfig: Returns a human-readable string representation of this configuration.
toString() - Method in record class org.ddolib.ddo.core.Decision: Returns a string representation of this record class.
toString() - Method in class org.ddolib.ddo.core.frontier.SimpleFrontier
toString() - Method in class org.ddolib.ddo.core.mdd.Edge: Returns a string representation of this edge, including origin, decision, and weight.
toString() - Method in class org.ddolib.ddo.core.mdd.Node: Returns a string representation of this node, including its value, suffix, best edge, and parent edges.
toString() - Method in class org.ddolib.ddo.core.mdd.NodeSubProblem
toString() - Method in class org.ddolib.ddo.core.SubProblem: Returns a human-readable representation of this subproblem, including its value, lower bound, f-value, depth, and state.
toString() - Method in class org.ddolib.examples.alp.ALPProblem
toString() - Method in class org.ddolib.examples.alp.ALPState: Returns a string representation of the ALP state.
toString() - Method in class org.ddolib.examples.alp.RunwayState
toString() - Method in class org.ddolib.examples.boundedknapsack.BKSProblem
toString() - Method in class org.ddolib.examples.gruler.GRProblem: Returns a human-readable representation of the problem instance.
toString() - Method in class org.ddolib.examples.gruler.GRState: Returns a human-readable string representation of this state.
toString() - Method in class org.ddolib.examples.knapsack.KSProblem
toString() - Method in class org.ddolib.examples.lcs.LCSProblem
toString() - Method in class org.ddolib.examples.lcs.LCSState: Returns a string representation of the state.
toString() - Method in class org.ddolib.examples.max2sat.BinaryClause
toString() - Method in class org.ddolib.examples.max2sat.Max2SatProblem
toString() - Method in record class org.ddolib.examples.max2sat.Max2SatState: Returns a string representation of this record class.
toString() - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns a string representation of the instance.
toString() - Method in record class org.ddolib.examples.maximumcoverage.MaxCoverState: Returns a string representation of the state.
toString() - Method in class org.ddolib.examples.mcp.Graph
toString() - Method in class org.ddolib.examples.mcp.MCPProblem
toString() - Method in record class org.ddolib.examples.mcp.MCPState: Returns a string representation of this record class.
toString() - Method in class org.ddolib.examples.misp.MispProblem
toString() - Method in class org.ddolib.examples.mks.MKSProblem: Returns a human-readable string representation of the problem, including capacities, items' profits, weights, and known optimal value.
toString() - Method in class org.ddolib.examples.mks.MKSState: Returns a string representation of this state.
toString() - Method in class org.ddolib.examples.msct.MSCTProblem: Returns a string representation of this MSCT instance for debugging purposes.
toString() - Method in record class org.ddolib.examples.msct.MSCTState: Returns a string representation of the state for debugging or logging purposes.
toString() - Method in class org.ddolib.examples.pdp.PDPProblem: Returns a string representation of the PDP instance.
toString() - Method in class org.ddolib.examples.pdp.PDPSolution: Returns a human-readable representation of the solution.
toString() - Method in class org.ddolib.examples.pdp.PDPState
toString() - Method in class org.ddolib.examples.pigmentscheduling.PSProblem
toString() - Method in class org.ddolib.examples.pigmentscheduling.PSState: Returns a string representation of the state, including current time, next item, and previous demands for debugging purposes.
toString() - Method in class org.ddolib.examples.smic.SMICProblem
toString() - Method in record class org.ddolib.examples.smic.SMICState: Returns a string representation of this state, displaying the set of remaining jobs, the current time, and the current inventory bounds.
toString() - Method in class org.ddolib.examples.srflp.SRFLPProblem
toString() - Method in record class org.ddolib.examples.srflp.SRFLPState: Returns a string representation of this record class.
toString() - Method in class org.ddolib.examples.talentscheduling.TSProblem
toString() - Method in record class org.ddolib.examples.talentscheduling.TSState: Returns a string representation of this record class.
toString() - Method in class org.ddolib.examples.tsp.TSPProblem: Returns a string representation of the instance.
toString() - Method in class org.ddolib.examples.tsp.TSPState
toString() - Method in record class org.ddolib.examples.tsptw.TimeWindow: Returns a string representation of this record class.
toString() - Method in record class org.ddolib.examples.tsptw.TSPTWDominanceKey: Returns a string representation of this record class.
toString() - Method in class org.ddolib.examples.tsptw.TSPTWProblem
toString() - Method in record class org.ddolib.examples.tsptw.TSPTWState: Returns a string representation of this TSPTW state, including position, time, must-visit and possibly-visit nodes, and depth.
toString() - Method in record class org.ddolib.util.StateAndDepth: Returns a string representation of this record class.
toSubProblem(Set<Decision>) - Method in class org.ddolib.ddo.core.mdd.NodeSubProblem: Converts this node-state association into an actual SubProblem.
transition(Integer, Decision) - Method in class org.ddolib.examples.boundedknapsack.BKSProblem: Computes the next state after making a decision on an item.
transition(Integer, Decision) - Method in class org.ddolib.examples.knapsack.KSProblem
transition(BitSet, Decision) - Method in class org.ddolib.examples.misp.MispProblem
transition(ALPState, Decision) - Method in class org.ddolib.examples.alp.ALPProblem
transition(GRState, Decision) - Method in class org.ddolib.examples.gruler.GRProblem: Computes the next state resulting from applying a decision (adding a new mark).
transition(LCSState, Decision) - Method in class org.ddolib.examples.lcs.LCSProblem: Computes the next state resulting from applying a decision at the current state.
transition(Max2SatState, Decision) - Method in class org.ddolib.examples.max2sat.Max2SatProblem
transition(MaxCoverState, Decision) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Applies a decision to a state to produce a new state.
transition(MCPState, Decision) - Method in class org.ddolib.examples.mcp.MCPProblem
transition(MKSState, Decision) - Method in class org.ddolib.examples.mks.MKSProblem: Computes the state resulting from taking a decision in the current state.
transition(MSCTState, Decision) - Method in class org.ddolib.examples.msct.MSCTProblem: Computes the next state resulting from scheduling a given job.
transition(PDPState, Decision) - Method in class org.ddolib.examples.pdp.PDPProblem: Computes the next state given a current state and a decision.
transition(PSState, Decision) - Method in class org.ddolib.examples.pigmentscheduling.PSProblem: Applies a production decision to the current state and returns the resulting new state.
transition(SMICState, Decision) - Method in class org.ddolib.examples.smic.SMICProblem: Applies a decision to transition from the current state to the next.
transition(SRFLPState, Decision) - Method in class org.ddolib.examples.srflp.SRFLPProblem
transition(TSState, Decision) - Method in class org.ddolib.examples.talentscheduling.TSProblem
transition(TSPState, Decision) - Method in class org.ddolib.examples.tsp.TSPProblem: Computes the next state after making a decision from the current state.
transition(TSPTWState, Decision) - Method in class org.ddolib.examples.tsptw.TSPTWProblem
transition(T, Decision) - Method in interface org.ddolib.modeling.Problem: Applies a decision to a state, computing the next state according to the problem's transition function.
transitionCost(Integer, Decision) - Method in class org.ddolib.examples.boundedknapsack.BKSProblem: Computes the transition cost associated with a decision.
transitionCost(Integer, Decision) - Method in class org.ddolib.examples.knapsack.KSProblem
transitionCost(BitSet, Decision) - Method in class org.ddolib.examples.misp.MispProblem
transitionCost(ALPState, Decision) - Method in class org.ddolib.examples.alp.ALPProblem
transitionCost(GRState, Decision) - Method in class org.ddolib.examples.gruler.GRProblem: Computes the cost associated with a transition between states.
transitionCost(LCSState, Decision) - Method in class org.ddolib.examples.lcs.LCSProblem: Computes the transition cost of a decision from the current state.
transitionCost(Max2SatState, Decision) - Method in class org.ddolib.examples.max2sat.Max2SatProblem
transitionCost(MaxCoverState, Decision) - Method in class org.ddolib.examples.maximumcoverage.MaxCoverProblem: Returns the cost of applying a decision to a state.
transitionCost(MCPState, Decision) - Method in class org.ddolib.examples.mcp.MCPProblem
transitionCost(MKSState, Decision) - Method in class org.ddolib.examples.mks.MKSProblem: Computes the cost of taking a decision in a given state.
transitionCost(MSCTState, Decision) - Method in class org.ddolib.examples.msct.MSCTProblem: Returns the cost of scheduling a given job from the current state.
transitionCost(PDPState, Decision) - Method in class org.ddolib.examples.pdp.PDPProblem: Computes the cost of transitioning from a state via a decision.
transitionCost(PSState, Decision) - Method in class org.ddolib.examples.pigmentscheduling.PSProblem: Computes the cost incurred by executing a given decision from the current state.
transitionCost(SMICState, Decision) - Method in class org.ddolib.examples.smic.SMICProblem: Computes the cost associated with scheduling a job from the current state.
transitionCost(SRFLPState, Decision) - Method in class org.ddolib.examples.srflp.SRFLPProblem
transitionCost(TSState, Decision) - Method in class org.ddolib.examples.talentscheduling.TSProblem
transitionCost(TSPState, Decision) - Method in class org.ddolib.examples.tsp.TSPProblem: Computes the transition cost of moving from the current state to the next state by visiting a given node.
transitionCost(TSPTWState, Decision) - Method in class org.ddolib.examples.tsptw.TSPTWProblem
transitionCost(T, Decision) - Method in interface org.ddolib.modeling.Problem: Computes the change in objective value resulting from applying a decision to a given state.
TSAcsMain - Class in org.ddolib.examples.talentscheduling: The talent scheduling problem (tsp) with Acs.
TSAcsMain() - Constructor for class org.ddolib.examples.talentscheduling.TSAcsMain
TSAstarMain - Class in org.ddolib.examples.talentscheduling: The talent scheduling problem (tsp) with AsTar.
TSAstarMain() - Constructor for class org.ddolib.examples.talentscheduling.TSAstarMain
TSDdoMain - Class in org.ddolib.examples.talentscheduling: The talent scheduling problem (tsp) with Ddo.
TSDdoMain() - Constructor for class org.ddolib.examples.talentscheduling.TSDdoMain
TSDistance - Class in org.ddolib.examples.talentscheduling
TSDistance(TSProblem) - Constructor for class org.ddolib.examples.talentscheduling.TSDistance
TSFastLowerBound - Class in org.ddolib.examples.talentscheduling: Implementation of a fast lower bound for the Talent Scheduling Problem (TSP).
TSFastLowerBound(TSProblem) - Constructor for class org.ddolib.examples.talentscheduling.TSFastLowerBound: Constructs a fast lower bound calculator for a given TSP problem.
TSLnsMain - Class in org.ddolib.examples.talentscheduling: Entry point for solving the Talent Scheduling (TalentSched) problem using a Large Neighborhood Search (LNS) approach.
TSLnsMain() - Constructor for class org.ddolib.examples.talentscheduling.TSLnsMain
TSPAcsMain - Class in org.ddolib.examples.tsp: The Traveling Salesman Problem (TSP) with Acs.
TSPAcsMain() - Constructor for class org.ddolib.examples.tsp.TSPAcsMain
TSPAstarMain - Class in org.ddolib.examples.tsp: The Traveling Salesman Problem (TSP) with AsTar.
TSPAstarMain() - Constructor for class org.ddolib.examples.tsp.TSPAstarMain
TSPDdoMain - Class in org.ddolib.examples.tsp: Main class to solve a Traveling Salesman Problem (TSP) instance using the Decision Diagram Optimization (DDO) method.
TSPDdoMain() - Constructor for class org.ddolib.examples.tsp.TSPDdoMain
TSPFastLowerBound - Class in org.ddolib.examples.tsp: Implementation of a fast lower bound for the Traveling Salesman Problem (TSP).
TSPFastLowerBound(TSPProblem) - Constructor for class org.ddolib.examples.tsp.TSPFastLowerBound: Constructs a fast lower bound calculator for the given TSP problem.
TSPGenerator - Class in org.ddolib.examples.tsp: Class to generate and handle instances of the Traveling Salesman Problem (TSP).
TSPGenerator(double[][]) - Constructor for class org.ddolib.examples.tsp.TSPGenerator: Constructs a TSP instance from a double[][] distance matrix.
TSPGenerator(int[][]) - Constructor for class org.ddolib.examples.tsp.TSPGenerator: Constructs a TSP instance from an int[][] distance matrix.
TSPGenerator(int[], int[]) - Constructor for class org.ddolib.examples.tsp.TSPGenerator: Constructs a Euclidean TSP instance from given x/y coordinates.
TSPGenerator(int, int, int) - Constructor for class org.ddolib.examples.tsp.TSPGenerator: Constructs a Euclidean TSP instance by randomly sampling coordinates in a square.
TSPLnsMain - Class in org.ddolib.examples.tsp: Entry point for solving the Traveling Salesman Problem (TSP) using a Large Neighborhood Search (LNS) approach.
TSPLnsMain() - Constructor for class org.ddolib.examples.tsp.TSPLnsMain
TSPLowerBound - Class in org.ddolib.util: Utility class to compute lower bounds for the Traveling Salesman Problem (TSP).
TSPLowerBound() - Constructor for class org.ddolib.util.TSPLowerBound
TSPProblem - Class in org.ddolib.examples.tsp: Class representing an instance of the Traveling Salesman Problem (TSP).
TSPProblem(double[][]) - Constructor for class org.ddolib.examples.tsp.TSPProblem: Constructs a TSP instance from a given distance matrix.
TSPProblem(double[][], double) - Constructor for class org.ddolib.examples.tsp.TSPProblem: Constructs a TSP instance from a given distance matrix and known optimal value.
TSPProblem(String) - Constructor for class org.ddolib.examples.tsp.TSPProblem: Constructs a TSP instance by reading an XML file in the XML-TSPLIB format.
TSPRanking - Class in org.ddolib.examples.tsp: Class that defines a ranking between two TSPState instances.
TSPRanking() - Constructor for class org.ddolib.examples.tsp.TSPRanking
TSPRelax - Class in org.ddolib.examples.tsp: Implementation of a relaxation for the Traveling Salesman Problem (TSP).
TSPRelax(TSPProblem) - Constructor for class org.ddolib.examples.tsp.TSPRelax: Constructs a relaxation for a given TSP problem.
TSProblem - Class in org.ddolib.examples.talentscheduling: The Talent Scheduling Problem (TSP) instance.
TSProblem(int, int, int[], int[], BitSet[], Optional<Double>) - Constructor for class org.ddolib.examples.talentscheduling.TSProblem: Constructs a TSP instance from explicit parameters.
TSProblem(String) - Constructor for class org.ddolib.examples.talentscheduling.TSProblem: Constructs a TSP instance by reading a file in the standard dataset format.
TSPState - Class in org.ddolib.examples.tsp: Represents a state in the Traveling Salesman Problem (TSP).
TSPState(BitSet, BitSet) - Constructor for class org.ddolib.examples.tsp.TSPState: Constructs a new TSPState.
TSPTWAcsMain - Class in org.ddolib.examples.tsptw: The Traveling Salesman Problem with Time Windows (TSP with Time Windows) with Acs.
TSPTWAcsMain() - Constructor for class org.ddolib.examples.tsptw.TSPTWAcsMain
TSPTWAstarMain - Class in org.ddolib.examples.tsptw: The Traveling Salesman Problem with Time Windows (TSP with Time Windows) with AsTar.
TSPTWAstarMain() - Constructor for class org.ddolib.examples.tsptw.TSPTWAstarMain
TSPTWAwAstarMain - Class in org.ddolib.examples.tsptw: The Traveling Salesman Problem with Time Windows (TSP with Time Windows) with Anytime Weighted A* (AWA*).
TSPTWAwAstarMain() - Constructor for class org.ddolib.examples.tsptw.TSPTWAwAstarMain
TSPTWDdoMain - Class in org.ddolib.examples.tsptw: The Traveling Salesman Problem with Time Windows (TSP with Time Windows) with Ddo.
TSPTWDdoMain() - Constructor for class org.ddolib.examples.tsptw.TSPTWDdoMain
TSPTWDominance - Class in org.ddolib.examples.tsptw: Dominance relation for the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWDominance() - Constructor for class org.ddolib.examples.tsptw.TSPTWDominance
TSPTWDominanceKey - Record Class in org.ddolib.examples.tsptw: Key used for dominance checking in the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWDominanceKey(Position, BitSet) - Constructor for record class org.ddolib.examples.tsptw.TSPTWDominanceKey: Creates an instance of a TSPTWDominanceKey record class.
TSPTWFastLowerBound - Class in org.ddolib.examples.tsptw: Implementation of a fast lower bound for the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWFastLowerBound(TSPTWProblem) - Constructor for class org.ddolib.examples.tsptw.TSPTWFastLowerBound: Constructs a fast lower bound calculator for a given TSPTW problem instance.
TSPTWLnsMain - Class in org.ddolib.examples.tsptw: Entry point for solving the Traveling Salesman Problem with Time Windows (TSPTW) using a Large Neighborhood Search (LNS) approach.
TSPTWLnsMain() - Constructor for class org.ddolib.examples.tsptw.TSPTWLnsMain
TSPTWProblem - Class in org.ddolib.examples.tsptw: Class representing an instance of the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWProblem(String) - Constructor for class org.ddolib.examples.tsptw.TSPTWProblem: Constructs a TSPTW problem instance from a data file.
TSPTWRanking - Class in org.ddolib.examples.tsptw: Ranking class for states in the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWRanking() - Constructor for class org.ddolib.examples.tsptw.TSPTWRanking
TSPTWRelax - Class in org.ddolib.examples.tsptw: Relaxation class for the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWRelax(TSPTWProblem) - Constructor for class org.ddolib.examples.tsptw.TSPTWRelax: Initializes the relaxation for a given TSPTW problem.
TSPTWState - Record Class in org.ddolib.examples.tsptw: Represents a state in the dynamic programming model for the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWState(Position, int, BitSet, BitSet, int) - Constructor for record class org.ddolib.examples.tsptw.TSPTWState: Creates an instance of a TSPTWState record class.
TSPTWWidth - Class in org.ddolib.examples.tsptw: Heuristic for computing the width of a layer in the dynamic programming model for the Traveling Salesman Problem with Time Windows (TSPTW).
TSPTWWidth(int, int) - Constructor for class org.ddolib.examples.tsptw.TSPTWWidth: Constructs a width heuristic for TSPTW layers.
TSRanking - Class in org.ddolib.examples.talentscheduling: Class that defines a ranking (ordering) between two TSState instances.
TSRanking() - Constructor for class org.ddolib.examples.talentscheduling.TSRanking
TSRelax - Class in org.ddolib.examples.talentscheduling: Implementation of a relaxation for the Talent Scheduling problem (TSP).
TSRelax(TSProblem) - Constructor for class org.ddolib.examples.talentscheduling.TSRelax: Constructs a new relaxation instance for the given Talent Scheduling problem.
TSState - Record Class in org.ddolib.examples.talentscheduling: Represents a state in the Talent Scheduling Problem (TalentSched).
TSState(BitSet, BitSet, BitSet) - Constructor for record class org.ddolib.examples.talentscheduling.TSState: Creates an instance of a TSState record class.
type - Variable in class org.ddolib.ddo.core.mdd.Node: The type of this node (e.g., exact, relaxed).

U

unassignedVars(int, Set<Decision>) - Static method in class org.ddolib.util.SolverUtil: Returns the set of variables not covered by the given set of decisions.
uncertaintyOnContent() - Method in class org.ddolib.examples.pdp.PDPState: Computes the uncertainty on the vehicle content, defined as maxContent - minContent.
UNCORRELATED - Enum constant in enum class org.ddolib.examples.boundedknapsack.BKSProblem.InstanceType
UNKNOWN - Enum constant in enum class org.ddolib.common.solver.SearchStatus
unrelatedNodes - Variable in class org.ddolib.examples.pdp.PDPProblem: Set of nodes that are not part of any pickup-delivery pair.
UNSAT - Enum constant in enum class org.ddolib.common.solver.SearchStatus
update(T, Threshold) - Method in class org.ddolib.ddo.core.cache.SimpleCache.Layer: Updates the threshold for a state if the new threshold is greater than the current.
updateDominance(T, int, double) - Method in class org.ddolib.common.dominance.DefaultDominanceChecker: Updates the dominance information for a given state.
updateDominance(T, int, double) - Method in class org.ddolib.common.dominance.DominanceChecker: Checks whether the input state is dominated and updates the front of non-dominated nodes.
updateDominance(T, int, double) - Method in class org.ddolib.common.dominance.SimpleDominanceChecker: Updates the dominance front at a given depth level based on the provided state.
updateThreshold(T, int, Threshold) - Method in interface org.ddolib.ddo.core.cache.Cache: Updates the threshold associated with a given state at a given depth.
updateThreshold(T, int, Threshold) - Method in class org.ddolib.ddo.core.cache.SimpleCache: Updates the threshold for a given state at a specified depth.
upperBound() - Method in interface org.ddolib.modeling.Model: Returns a precomputed upper bound on the optimal value.
useCache() - Method in interface org.ddolib.modeling.DdoModel: Indicates whether caching should be used during the diagram construction.
useCache() - Method in class org.ddolib.modeling.ExactModel
useCache(boolean) - Method in interface org.ddolib.modeling.DdoModel: Returns a copy of this model by enabling or disabling the cache.
useLNS - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Indicates whether Large Neighborhood Search (LNS) should be used to improve solutions during compilation.
useLNS() - Method in interface org.ddolib.modeling.DdoModel
useLNS() - Method in interface org.ddolib.modeling.LnsModel: Indicates whether LNS should be used.

V

value - Variable in class org.ddolib.ddo.core.mdd.Node: The length of the longest path to this node.
value - Variable in class org.ddolib.examples.pdp.PDPSolution: The total value (cost or distance) of the solution.
value() - Method in class org.ddolib.common.solver.Solution: Returns the evaluation of the objective value of this solution.
value() - Method in record class org.ddolib.ddo.core.Decision: Returns the value of the value record component.
value(T) - Method in interface org.ddolib.modeling.DominanceKey: Returns the dominance key associated with the given state.
valueOf(String) - Static method in enum class org.ddolib.common.solver.SearchStatus: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.ddolib.ddo.core.compilation.CompilationType: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.ddolib.ddo.core.frontier.CutSetType: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.ddolib.ddo.core.mdd.NodeType: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.ddolib.examples.boundedknapsack.BKSProblem.InstanceType: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.ddolib.util.debug.DebugLevel: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class org.ddolib.util.verbosity.VerbosityLevel: Returns the enum constant of this class with the specified name.
values - Variable in class org.ddolib.examples.boundedknapsack.BKSProblem
values() - Static method in enum class org.ddolib.common.solver.SearchStatus: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.ddolib.ddo.core.compilation.CompilationType: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.ddolib.ddo.core.frontier.CutSetType: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.ddolib.ddo.core.mdd.NodeType: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.ddolib.examples.boundedknapsack.BKSProblem.InstanceType: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.ddolib.util.debug.DebugLevel: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class org.ddolib.util.verbosity.VerbosityLevel: Returns an array containing the constants of this enum class, in the order they are declared.
variable() - Method in record class org.ddolib.ddo.core.Decision: Returns the value of the variable record component.
variableHeuristic - Variable in class org.ddolib.ddo.core.compilation.CompilationConfig: Heuristic used to select the next variable to branch on during compilation.
variableHeuristic() - Method in class org.ddolib.modeling.ExactModel
variableHeuristic() - Method in interface org.ddolib.modeling.Model: Returns the heuristic used to determine the next variable to branch on during decision diagram compilation.
VariableHeuristic<T> - Interface in org.ddolib.ddo.core.heuristics.variable: Defines a strategy for selecting the next decision variable to branch on during the construction or exploration of a decision diagram.
VerboseMode - Class in org.ddolib.util.verbosity: Utility class for printing detailed information about the search process based on a specified VerbosityLevel.
VerboseMode(VerbosityLevel, long) - Constructor for class org.ddolib.util.verbosity.VerboseMode: Creates a VerboseMode instance with a given verbosity level and interval for printing frontier statistics.
verbosityLevel() - Method in interface org.ddolib.modeling.Model: Returns the verbosity level of the solver when this model is executed.
VerbosityLevel - Enum Class in org.ddolib.util.verbosity: Defines the different verbosity levels controlling the amount of information printed during the execution of a solver.

W

WEAKLY_CORRELATED - Enum constant in enum class org.ddolib.examples.boundedknapsack.BKSProblem.InstanceType
weight - Variable in class org.ddolib.ddo.core.mdd.Edge: The weight of the edge.
weight - Variable in class org.ddolib.examples.knapsack.KSProblem: Weights of the items.
weight - Variable in class org.ddolib.examples.misp.MispProblem: For each node i, weight[i] contains the weight associated with i.
weight() - Method in interface org.ddolib.modeling.AwAstarModel: Returns the weight to add to the heuristic function.
weight(int, int) - Method in class org.ddolib.examples.max2sat.Max2SatProblem: Returns the weight of a binary clause (x, y), considering commutativity.
weightedJaccardDistance(BitSet, BitSet, double[]) - Static method in class org.ddolib.util.DistanceUtil: Computes the weighted Jaccard Distance between the two given sets.
weightedSymmetricDifferenceDistance(BitSet, BitSet, double[]) - Static method in class org.ddolib.util.DistanceUtil: Computes the weighted symmetric difference between a and b
weightOf(int, int) - Method in class org.ddolib.examples.mcp.Graph: Given two nodes, returns the weight of their edges.
weights - Variable in class org.ddolib.examples.boundedknapsack.BKSProblem
widthHeuristic() - Method in interface org.ddolib.modeling.DdoModel: Returns the width heuristic controlling the maximum number of nodes per layer.
widthHeuristic() - Method in class org.ddolib.modeling.ExactModel
widthHeuristic() - Method in interface org.ddolib.modeling.LnsModel: Returns the width heuristic used for tree exploration.
WidthHeuristic<T> - Interface in org.ddolib.ddo.core.heuristics.width: Interface for heuristics that determine the maximum width of a layer in a multi-valued decision diagram (MDD).
writeInstance(String, int, int, int, Random) - Method in class org.ddolib.examples.pdp.PDPGenerator: Generates a PDP instance and writes it to a file in a human-readable format.
writeInstance(String, int, long) - Static method in class org.ddolib.examples.msct.MSCTGenerator: Generates and writes instances for the MSCT
writeRandomInstance(String, int, int, boolean) - Static method in class org.ddolib.examples.mcp.MCPGenerator: Randomly generates and save instance of MCP into the given file.
writeRandomInstance(String, int, int, boolean, long) - Static method in class org.ddolib.examples.mcp.MCPGenerator: Randomly generates and save instance of MCP into the given file.

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