Uses of Class
org.tweetyproject.math.term.ElementOfCombinatoricsProb
Package
Description
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Uses of ElementOfCombinatoricsProb in org.tweetyproject.math.examples
Modifier and TypeMethodDescriptionKnapSack.createRandomNewSolution(ArrayList<ElementOfCombinatoricsProb> currSol)
TravelingSalesman.createRandomNewSolution(ArrayList<ElementOfCombinatoricsProb> currSol)
Modifier and TypeMethodDescriptionKnapSack.getHeuristicValue(ElementOfCombinatoricsProb solutionComponent, Integer getCurrentIndex, ElementOfCombinatoricsProb initialReference, ElementOfCombinatoricsProb[] sol)
since this class is not used with ant optimization, we do not need this methodTravelingSalesman.getHeuristicValue(ElementOfCombinatoricsProb solutionComponent, Integer getCurrentIndex, ElementOfCombinatoricsProb initialReference, ElementOfCombinatoricsProb[] sol)
Modifier and TypeMethodDescriptionKnapSack.createRandomNewSolution(ArrayList<ElementOfCombinatoricsProb> currSol)
TravelingSalesman.createRandomNewSolution(ArrayList<ElementOfCombinatoricsProb> currSol)
double
KnapSack.evaluate(ArrayList<ElementOfCombinatoricsProb> sol)
double
TravelingSalesman.evaluate(ArrayList<ElementOfCombinatoricsProb> sol)
boolean
KnapSack.isValid(ArrayList<ElementOfCombinatoricsProb> sol)
boolean
TravelingSalesman.isValid(ArrayList<ElementOfCombinatoricsProb> solution)
double
KnapSack.sumOfValues(ArrayList<ElementOfCombinatoricsProb> sol)
calculates sum of valuesdouble
KnapSack.sumOfWeights(ArrayList<ElementOfCombinatoricsProb> sol)
double
TravelingSalesman.sumOfWeights(ArrayList<ElementOfCombinatoricsProb> sol)
ModifierConstructorDescriptionKnapSack(ArrayList<ElementOfCombinatoricsProb> elements, Term maxWeight)
constructorTravelingSalesman(ArrayList<ElementOfCombinatoricsProb> elements)
constructor -
Uses of ElementOfCombinatoricsProb in org.tweetyproject.math.opt.problem
Modifier and TypeMethodDescriptionCombinatoricsProblem.createDifference(ArrayList<ElementOfCombinatoricsProb> c)
abstract ArrayList<ElementOfCombinatoricsProb>
CombinatoricsProblem.createRandomNewSolution(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 solutionCombinatoricsProblem.formNeighborhood(ArrayList<ElementOfCombinatoricsProb> currSol, int minIterations, int maxIteration, double threshold)
Modifier and TypeMethodDescriptionabstract Double
CombinatoricsProblem.getHeuristicValue(ElementOfCombinatoricsProb solutionComponent, Integer getCurrentIndex, ElementOfCombinatoricsProb initialReference, ElementOfCombinatoricsProb[] sol)
for Ant optimization: give a chance between 0 and 1 for accepting solutionComponent to the solution solModifier and TypeMethodDescriptionCombinatoricsProblem.createDifference(ArrayList<ElementOfCombinatoricsProb> c)
abstract ArrayList<ElementOfCombinatoricsProb>
CombinatoricsProblem.createRandomNewSolution(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 solutionabstract double
CombinatoricsProblem.evaluate(ArrayList<ElementOfCombinatoricsProb> sol)
evaluates the solutionCombinatoricsProblem.formNeighborhood(ArrayList<ElementOfCombinatoricsProb> currSol, int minIterations, int maxIteration, double threshold)
abstract boolean
CombinatoricsProblem.isValid(ArrayList<ElementOfCombinatoricsProb> sol)
checks if a given solution is valid under all constraintsabstract double
CombinatoricsProblem.sumOfWeights(ArrayList<ElementOfCombinatoricsProb> sol)
ModifierConstructorDescriptionCombinatoricsProblem(List<ElementOfCombinatoricsProb> elements, int[][] graphRepresantation)
constructor -
Uses of ElementOfCombinatoricsProb in org.tweetyproject.math.opt.solver
Modifier and TypeMethodDescriptionIteratedLocalSearch.bestNeighbor(ArrayList<ElementOfCombinatoricsProb> currSol)
performs one step of a local searchStochasticLocalSearch.findbestNeighbor(ArrayList<ArrayList<ElementOfCombinatoricsProb>> neighbors)
StochasticLocalSearch.findrandomNeighbor(ArrayList<ArrayList<ElementOfCombinatoricsProb>> neighbors)
isula.aco.AntColony<ElementOfCombinatoricsProb,AntColonyOptimization.AntCol_Environment>
AntColonyOptimization.getAntColony(isula.aco.ConfigurationProvider configurationProvider)
Ant colonyIteratedLocalSearch.pertubate(ArrayList<ElementOfCombinatoricsProb> currSol)
changes the solution drastically to escape a local minimumAntColonyOptimization.solve(CombinatoricsProblem prob)
solves the problem and connects the config and initializes the restIteratedLocalSearch.solve(CombinatoricsProblem prob)
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).SimulatedAnnealing.solve(CombinatoricsProblem prob)
StochasticLocalSearch.solve(CombinatoricsProblem prob)
TabuSearch.solve(CombinatoricsProblem prob)
Modifier and TypeMethodDescriptionIteratedLocalSearch.bestNeighbor(ArrayList<ElementOfCombinatoricsProb> currSol)
performs one step of a local searchint
SimpleGeneticOptimizationSolverCombinatorics.FitnessComparator.compare(ArrayList<ElementOfCombinatoricsProb> ind1, ArrayList<ElementOfCombinatoricsProb> ind2)
StochasticLocalSearch.findbestNeighbor(ArrayList<ArrayList<ElementOfCombinatoricsProb>> neighbors)
StochasticLocalSearch.findrandomNeighbor(ArrayList<ArrayList<ElementOfCombinatoricsProb>> neighbors)
IteratedLocalSearch.pertubate(ArrayList<ElementOfCombinatoricsProb> currSol)
changes the solution drastically to escape a local minimum