Class SimulatedAnnealingOnConstrProb
java.lang.Object
org.tweetyproject.math.opt.solver.Solver
org.tweetyproject.math.opt.solver.SimulatedAnnealingOnConstrProb
implements the Simulated Annealing algorithm
 for optimization problems
- Author:
- Sebastian Franke
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Constructor SummaryConstructorsConstructorDescriptionSimulatedAnnealingOnConstrProb(double startTemp, double decreasePerIt, int maxStepsWithNoImprove) Constructor
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Method SummaryModifier and TypeMethodDescriptionchooseANeighbor(Map<Variable, Term> currSol, int minIterations, int maxIterations, double threshold, Term targetFunc) Computes a solution to the given constraint satisfaction or optimization problem, i.e.Methods inherited from class org.tweetyproject.math.opt.solver.SolvergetDefaultGeneralSolver, getDefaultIntegerLinearSolver, getDefaultLinearSolver, hasDefaultGeneralSolver, hasDefaultIntegerLinearSolver, hasDefaultLinearSolver, isInstalled, setDefaultGeneralSolver, setDefaultIntegerLinearSolver, setDefaultLinearSolver
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Constructor Details- 
SimulatedAnnealingOnConstrProbpublic SimulatedAnnealingOnConstrProb(double startTemp, double decreasePerIt, int maxStepsWithNoImprove) Constructor- Parameters:
- startTemp- startTemp
- decreasePerIt- decreasePerIt
- maxStepsWithNoImprove- maxStepsWithNoImprove
 
 
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Method Details- 
chooseANeighborpublic Map<Variable,Term> chooseANeighbor(Map<Variable, Term> currSol, int minIterations, int maxIterations, double threshold, Term targetFunc) - Parameters:
- currSol- : the solution that every newly created solution uses as a initial solution in createNewSol
- minIterations- : the minimum amount of solutions to be created
- maxIterations- : the maximum amount of solutions to be created
- threshold- : if a solution with the quality of threshold is reached we do maximum 10 more tries
- targetFunc- the target function
- Returns:
- the best solution that was found and is a mutant of currSol
 
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solveDescription copied from class:SolverComputes a solution to the given constraint satisfaction or optimization problem, i.e. a mapping from variables of the problem to terms.
 
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