Uses of Class
org.tweetyproject.math.term.ElementOfCombinatoricsProb

Packages that use ElementOfCombinatoricsProb

Package	Description
org.tweetyproject.math.examples
org.tweetyproject.math.opt.problem
org.tweetyproject.math.opt.solver

Uses of ElementOfCombinatoricsProb in org.tweetyproject.math.examples

Methods in org.tweetyproject.math.examples that return types with arguments of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
java.util.ArrayList<ElementOfCombinatoricsProb>	KnapSack.createRandomNewSolution(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)
java.util.ArrayList<ElementOfCombinatoricsProb>	TravelingSalesman.createRandomNewSolution(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)

Methods in org.tweetyproject.math.examples with parameters of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
java.lang.Double	KnapSack.getHeuristicValue(ElementOfCombinatoricsProb solutionComponent, java.lang.Integer getCurrentIndex, ElementOfCombinatoricsProb initialReference, ElementOfCombinatoricsProb[] sol)	since this class is not used with ant optimization, we do not need this method
java.lang.Double	TravelingSalesman.getHeuristicValue(ElementOfCombinatoricsProb solutionComponent, java.lang.Integer getCurrentIndex, ElementOfCombinatoricsProb initialReference, ElementOfCombinatoricsProb[] sol)

Method parameters in org.tweetyproject.math.examples with type arguments of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
java.util.ArrayList<ElementOfCombinatoricsProb>	KnapSack.createRandomNewSolution(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)
java.util.ArrayList<ElementOfCombinatoricsProb>	TravelingSalesman.createRandomNewSolution(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)
double	KnapSack.evaluate(java.util.ArrayList<ElementOfCombinatoricsProb> sol)
double	TravelingSalesman.evaluate(java.util.ArrayList<ElementOfCombinatoricsProb> sol)
boolean	KnapSack.isValid(java.util.ArrayList<ElementOfCombinatoricsProb> sol)
boolean	TravelingSalesman.isValid(java.util.ArrayList<ElementOfCombinatoricsProb> solution)
double	KnapSack.sumOfValues(java.util.ArrayList<ElementOfCombinatoricsProb> sol)
double	KnapSack.sumOfWeights(java.util.ArrayList<ElementOfCombinatoricsProb> sol)
double	TravelingSalesman.sumOfWeights(java.util.ArrayList<ElementOfCombinatoricsProb> sol)

Constructor parameters in org.tweetyproject.math.examples with type arguments of type ElementOfCombinatoricsProb

Constructor	Description
KnapSack(java.util.ArrayList<ElementOfCombinatoricsProb> elements, Term maxWeight)
TravelingSalesman(java.util.ArrayList<ElementOfCombinatoricsProb> elements)

Uses of ElementOfCombinatoricsProb in org.tweetyproject.math.opt.problem

Fields in org.tweetyproject.math.opt.problem with type parameters of type ElementOfCombinatoricsProb

Modifier and Type	Field	Description
java.util.List<ElementOfCombinatoricsProb>	CombinatoricsProblem.elements

Methods in org.tweetyproject.math.opt.problem that return types with arguments of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
java.util.ArrayList<ElementOfCombinatoricsProb>	CombinatoricsProblem.createDifference(java.util.ArrayList<ElementOfCombinatoricsProb> c)
abstract java.util.ArrayList<ElementOfCombinatoricsProb>	CombinatoricsProblem.createRandomNewSolution(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)	create a solution that changes the solution currSol a little bit (i.e.: for TSP: swap 2 cities; for KnapSack: add a random element) for currSol == null: create a random solution
java.util.ArrayList<java.util.ArrayList<ElementOfCombinatoricsProb>>	CombinatoricsProblem.formNeighborhood(java.util.ArrayList<ElementOfCombinatoricsProb> currSol, int minIterations, int maxIteration, double threshold)

Methods in org.tweetyproject.math.opt.problem with parameters of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
abstract java.lang.Double	CombinatoricsProblem.getHeuristicValue(ElementOfCombinatoricsProb solutionComponent, java.lang.Integer getCurrentIndex, ElementOfCombinatoricsProb initialReference, ElementOfCombinatoricsProb[] sol)	for Ant optimization: give a chance between 0 and 1 for accepting solutionComponent to the solution sol

Method parameters in org.tweetyproject.math.opt.problem with type arguments of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
java.util.ArrayList<ElementOfCombinatoricsProb>	CombinatoricsProblem.createDifference(java.util.ArrayList<ElementOfCombinatoricsProb> c)
abstract java.util.ArrayList<ElementOfCombinatoricsProb>	CombinatoricsProblem.createRandomNewSolution(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)	create a solution that changes the solution currSol a little bit (i.e.: for TSP: swap 2 cities; for KnapSack: add a random element) for currSol == null: create a random solution
abstract double	CombinatoricsProblem.evaluate(java.util.ArrayList<ElementOfCombinatoricsProb> sol)	evaluates the solution
java.util.ArrayList<java.util.ArrayList<ElementOfCombinatoricsProb>>	CombinatoricsProblem.formNeighborhood(java.util.ArrayList<ElementOfCombinatoricsProb> currSol, int minIterations, int maxIteration, double threshold)
abstract boolean	CombinatoricsProblem.isValid(java.util.ArrayList<ElementOfCombinatoricsProb> sol)	checks if a given solution is valid under all constraints
abstract double	CombinatoricsProblem.sumOfWeights(java.util.ArrayList<ElementOfCombinatoricsProb> sol)

Constructor parameters in org.tweetyproject.math.opt.problem with type arguments of type ElementOfCombinatoricsProb

Constructor	Description
CombinatoricsProblem(java.util.List<ElementOfCombinatoricsProb> elements, int[][] graphRepresantation)

Uses of ElementOfCombinatoricsProb in org.tweetyproject.math.opt.solver

Methods in org.tweetyproject.math.opt.solver that return types with arguments of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
java.util.ArrayList<ElementOfCombinatoricsProb>	IteratedLocalSearch.bestNeighbor(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)	performs one step of a local search
java.util.ArrayList<ElementOfCombinatoricsProb>	StochasticLocalSearch.findbestNeighbor(java.util.ArrayList<java.util.ArrayList<ElementOfCombinatoricsProb>> neighbors)
java.util.ArrayList<ElementOfCombinatoricsProb>	StochasticLocalSearch.findrandomNeighbor(java.util.ArrayList<java.util.ArrayList<ElementOfCombinatoricsProb>> neighbors)
isula.aco.AntColony<ElementOfCombinatoricsProb,AntColonyOptimization.AntCol_Environment>	AntColonyOptimization.getAntColony(isula.aco.ConfigurationProvider configurationProvider)	Ant colony
java.util.ArrayList<ElementOfCombinatoricsProb>	IteratedLocalSearch.pertubate(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)	changes the solution drastically to escape a local minimum
java.util.ArrayList<ElementOfCombinatoricsProb>	AntColonyOptimization.solve(CombinatoricsProblem prob)	solves the problem and connects the config and initializes the rest
java.util.ArrayList<ElementOfCombinatoricsProb>	IteratedLocalSearch.solve(CombinatoricsProblem prob)
java.util.ArrayList<ElementOfCombinatoricsProb>	SimpleGeneticOptimizationSolverCombinatorics.solve(CombinatoricsProblem prob)	Returns the solution according the problem; problem has to be minimizing (which only contains variables with defined upper and lower bounds).
java.util.ArrayList<ElementOfCombinatoricsProb>	SimulatedAnnealing.solve(CombinatoricsProblem prob)
java.util.ArrayList<ElementOfCombinatoricsProb>	StochasticLocalSearch.solve(CombinatoricsProblem prob)
java.util.ArrayList<ElementOfCombinatoricsProb>	TabuSearch.solve(CombinatoricsProblem prob)

Method parameters in org.tweetyproject.math.opt.solver with type arguments of type ElementOfCombinatoricsProb

Modifier and Type	Method	Description
java.util.ArrayList<ElementOfCombinatoricsProb>	IteratedLocalSearch.bestNeighbor(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)	performs one step of a local search
int	SimpleGeneticOptimizationSolverCombinatorics.FitnessComparator.compare(java.util.ArrayList<ElementOfCombinatoricsProb> ind1, java.util.ArrayList<ElementOfCombinatoricsProb> ind2)
java.util.ArrayList<ElementOfCombinatoricsProb>	StochasticLocalSearch.findbestNeighbor(java.util.ArrayList<java.util.ArrayList<ElementOfCombinatoricsProb>> neighbors)
java.util.ArrayList<ElementOfCombinatoricsProb>	StochasticLocalSearch.findrandomNeighbor(java.util.ArrayList<java.util.ArrayList<ElementOfCombinatoricsProb>> neighbors)
java.util.ArrayList<ElementOfCombinatoricsProb>	IteratedLocalSearch.pertubate(java.util.ArrayList<ElementOfCombinatoricsProb> currSol)	changes the solution drastically to escape a local minimum