Solver

org.ddolibscala.solver.Solver
See theSolver companion class
object Solver

Factory for solvers

Attributes

Companion
class
Graph
Supertypes
class Object
trait Matchable
class Any
Self type
Solver.type

Members list

Value members

Concrete methods

def acs[T](problem: Problem[T], columnWidth: Int = ..., lowerBound: FastLowerBound[T] = ..., upperBound: Double = ..., dominance: DominanceChecker[T] = ..., variableHeuristic: VariableHeuristic[T] = ..., verbosityLvl: VerbosityLvl = ..., debugMode: DebugMode = ...): Solver

Instantiates and returns an Anytime column search (ACS) solver

Instantiates and returns an Anytime column search (ACS) solver

Type parameters

T

the type representing a state in the problem

Value parameters

columnWidth

column width used for formatted output during the Anytime Column Search process

debugMode

the debugging level to apply during the compilation and solving phases

dominance

the dominance checker used to prune dominated states from the search space

lowerBound

a heuristic that estimates a lower bound on the objective value for a given state

problem

the structure defining the structure, transitions, and objective function of the optimization task

upperBound

a precomputed upper used to start pruning earlier

variableHeuristic

the heuristic used to determine the next variable to branch on during decision diagram compilation

verbosityLvl

the verbosity level of the solver when this model is executed

Attributes

Returns

a solver based on the ACS algorithm

def astar[T](problem: Problem[T], lowerBound: FastLowerBound[T] = ..., upperBound: Double = ..., dominance: DominanceChecker[T] = ..., variableHeuristic: VariableHeuristic[T] = ..., verbosityLvl: VerbosityLvl = ..., debugMode: DebugMode = ...): Solver

Instantiates and returns an A* solver.

Instantiates and returns an A* solver.

Type parameters

T

the type representing a state in the problem

Value parameters

debugMode

the debugging level to apply during the compilation and solving phases

dominance

the dominance checker used to prune dominated states from the search space

lowerBound

a heuristic that estimates a lower bound on the objective value for a given state

problem

the structure defining the structure, transitions, and objective function of the optimization task

upperBound

a precomputed upper bound used to start pruning earlier

variableHeuristic

the heuristic used to determine the next variable to branch on during decision diagram compilation

verbosityLvl

the verbosity level of the solver when this model is executed

Attributes

Returns

a solver based on the A* algorithm

def ddo[T](problem: Problem[T], relaxation: Relaxation[T], lowerBound: FastLowerBound[T] = ..., upperBound: Double = ..., dominance: DominanceChecker[T] = ..., ranking: StateRanking[T] = ..., widthHeuristic: WidthHeuristic[T] = ..., frontier: CutSetType = ..., useCache: Boolean = ..., exportDot: Boolean = ..., variableHeuristic: VariableHeuristic[T] = ..., verbosityLvl: VerbosityLvl = ..., debugMode: DebugMode = ...): Solver

Instantiates and returns a DDO solver.

Instantiates and returns a DDO solver.

Type parameters

T

the type representing a state in the problem

Value parameters

debugMode

the debugging level to apply during the compilation and solving phases

dominance

the dominance checker used to prune dominated states from the search space

exportDot

whether the generated diagram must be exported to DOT file

frontier

type of frontier management strategy used to store and expand the current layer of the decision diagram

lowerBound

a heuristic that estimates a lower bound on the objective value for a given state

problem

the structure defining the structure, transitions, and objective function of the optimization task

ranking

the heuristic used to determine the next variable to branch on during decision diagram compilation

relaxation

the relaxation of the model used to evaluate the nodes or layers of the decision diagram

upperBound

a precomputed upper bound used to start pruning earlier

useCache

whether caching mechanism must be used

variableHeuristic

the heuristic used to determine the next variable to branch on during decision diagram compilation

verbosityLvl

the verbosity level of the solver when this model is executed

widthHeuristic

heuristic controlling the maximum number of nodes per layer

Attributes

Returns

a solver based on the DDO algorithm

def exact[T](problem: Problem[T], lowerBound: FastLowerBound[T] = ..., dominance: DominanceChecker[T] = ..., verbosityLvl: VerbosityLvl = ..., debugMode: DebugMode = ..., exportDot: Boolean = ...): Solver

Instantiates and returns an exact solver.

Instantiates and returns an exact solver.

Type parameters

T

the type representing a state in the problem

Value parameters

debugMode

the debugging level to apply during the compilation and solving phases

dominance

the dominance checker used to prune dominated states from the search space

exportDot

whether the generated diagram must be exported to DOT file

lowerBound

a heuristic that estimates a lower bound on the objective value for a given state

problem

the structure defining the structure, transitions, and objective function of the optimization task

verbosityLvl

the verbosity level of the solver when this model is executed

Attributes

Returns

a solver that generate a complete decision diagram to solve the problem