Uses of Class
org.ddolib.examples.mks.MKSState

Packages that use MKSState

Package	Description
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 $(C_1,\ldots ,C_m)$.

Uses of MKSState in org.ddolib.examples.mks

Methods in org.ddolib.examples.mks that return MKSState

Modifier and Type	Method	Description
MKSState	MKSState.clone()	Creates a deep copy of this state.
MKSState	MKSProblem.initialState()	Returns the initial state for this problem, representing full capacities.
MKSState	MKSRelax.mergeStates(Iterator<MKSState> states)	Merges multiple MKS states into a single relaxed state.
MKSState	MKSProblem.transition(MKSState state, Decision decision)	Computes the state resulting from taking a decision in the current state.

Methods in org.ddolib.examples.mks with parameters of type MKSState

Modifier and Type	Method	Description
int	MKSRanking.compare(MKSState o1, MKSState o2)	Compares two MKS states based on their average remaining capacities.
double	MKSDistance.distance(MKSState a, MKSState b)	Computes the normalized Euclidean distance between two MKS states.
double	MKSDistance.distanceWithRoot(MKSState a)	Computes the normalized Euclidean distance from the given state to the initial state.
Iterator<Integer>	MKSProblem.domain(MKSState state, int var)	Returns an iterator over the domain of a variable (item) in a given state.
double	MKSFastLowerBound.fastLowerBound(MKSState state, Set<Integer> variables)	Computes a fast lower bound for a given state and a set of variables (items).
Integer	MKSDominance.getKey(MKSState state)	Returns a key for grouping states in dominance checks.
boolean	MKSDominance.isDominatedOrEqual(MKSState state1, MKSState state2)	Determines whether state1 is dominated by or equal to state2.
double	MKSRelax.relaxEdge(MKSState from, MKSState to, MKSState merged, Decision d, double cost)	Returns the cost of an edge in the relaxed decision diagram.
MKSState	MKSProblem.transition(MKSState state, Decision decision)	Computes the state resulting from taking a decision in the current state.
double	MKSProblem.transitionCost(MKSState state, Decision decision)	Computes the cost of taking a decision in a given state.

Method parameters in org.ddolib.examples.mks with type arguments of type MKSState

Modifier and Type	Method	Description
MKSState	MKSRelax.mergeStates(Iterator<MKSState> states)	Merges multiple MKS states into a single relaxed state.