Module org.cicirello.chips_n_salsa
Package org.cicirello.search.concurrent

Interface Splittable<T extends Splittable<T>>

Type Parameters:
T - The type of object that supports splitting.
All Known Subinterfaces:
AnnealingSchedule, ConstructiveHeuristic<T>, CrossoverOperator<T>, Initializer<T>, IterableMutationOperator<T>, Metaheuristic<T>, MutationOperator<T>, ReoptimizableMetaheuristic<T>, RestartSchedule, SelectionOperator, SimpleLocalMetaheuristic<T>, SimpleMetaheuristic<T>, SingleSolutionMetaheuristic<T>, TrackableSearch<T>, UndoableMutationOperator<T>
All Known Implementing Classes:
AcceptanceBandSampling, AcceptanceTracker, AdaptiveEvolutionaryAlgorithm, AdaptiveMutationOnlyEvolutionaryAlgorithm, AdjacentSwapMutation, ApparentTardinessCost, ApparentTardinessCostSetupAdjusted, ATCS, BiasedFitnessProportionalSelection, BiasedStochasticUniversalSampling, BitFlipMutation, BitVectorInitializer, BlockInterchangeMutation, BlockMoveMutation, BoltzmannSelection, BoltzmannStochasticUniversalSampling, BoundMax, CauchyMutation, ConstantRestartSchedule, CycleAlphaMutation, CycleCrossover, CycleMutation, DefiniteBitFlipMutation, DynamicATCS, EarliestDueDate, EdgeRecombination, EnhancedEdgeRecombination, ExponentialCooling, ExponentialEarlyTardyHeuristic, ExponentialRankSelection, ExponentialRankStochasticUniversalSampling, FirstDescentHillClimber, FitnessProportionalSelection, FitnessShifter, ForresterEtAl2008, GaussianMutation, GenerationalEvolutionaryAlgorithm, GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators, GenerationalMutationOnlyEvolutionaryAlgorithm, GeneticAlgorithm, GramacyLee2012, HeuristicBiasedStochasticSampling, HeuristicPermutationGenerator, HeuristicSolutionGenerator, HybridConstructiveHeuristic, HybridCrossover, HybridMutation, HybridUndoableMutation, InitializeBySimpleMetaheuristic, InsertionMutation, IntegerValueInitializer, IntegerVectorInitializer, IterativeSampling, KPointCrossover, KPointCrossover, KPointCrossover, LinearCooling, LinearEarlyTardyHeuristic, LinearRankSelection, LinearRankStochasticUniversalSampling, LogarithmicCooling, LubyRestarts, MinimumSlackTime, ModifiedLam, ModifiedLamOriginal, Montagne, Multistarter, MutationOnlyGeneticAlgorithm, NaiveGenerationalEvolutionaryAlgorithm, NearestCityHeuristic, NearestCityPairHeuristic, NonWrappingOrderCrossover, OnePlusOneEvolutionaryAlgorithm, OnePlusOneGeneticAlgorithm, OrderCrossover, OrderCrossoverTwo, ParallelMetaheuristic, ParallelMultistarter, ParallelReoptimizableMetaheuristic, ParallelReoptimizableMultistarter, ParallelVariableAnnealingLength, ParameterFreeExponentialCooling, ParameterFreeLinearCooling, PartiallyMatchedCrossover, PermutationInitializer, PermutationToBitVectorProblem, PermutationToBitVectorProblem.DoubleCost, PermutationToBitVectorProblem.IntegerCost, PositionBasedCrossover, PrecedencePreservativeCrossover, RandomSelection, RandomValueChangeMutation, RealValueInitializer, RealVectorInitializer, ReoptimizableMultistarter, ReversalMutation, RotationMutation, ScrambleMutation, SelfTuningLam, ShortestProcessingPlusSetupTime, ShortestProcessingPlusSetupTimePrecompute, ShortestProcessingTime, SigmaScaling, SimpleGeneticAlgorithm, SimulatedAnnealing, SinglePointCrossover, SinglePointCrossover, SinglePointCrossover, SmallestNormalizedSetup, SmallestSetup, SmallestSetupPrecompute, SmallestTwoJobSetup, SteepestDescentHillClimber, StochasticUniversalSampling, SwapMutation, ThreeOptMutation, TimedParallelMultistarter, TimedParallelReoptimizableMultistarter, TournamentSelection, TruncationSelection, TwoChangeMutation, TwoPointCrossover, TwoPointCrossover, TwoPointCrossover, UndoableCauchyMutation, UndoableGaussianMutation, UndoableRandomValueChangeMutation, UndoableScrambleMutation, UndoableUniformMutation, UndoableUniformMutation, UndoableUniformScrambleMutation, UniformCrossover, UniformCrossover, UniformCrossover, UniformMutation, UniformMutation, UniformOrderBasedCrossover, UniformPartiallyMatchedCrossover, UniformPrecedencePreservativeCrossover, UniformScrambleMutation, ValueBiasedStochasticSampling, VariableAnnealingLength, WeightedCostOverTime, WeightedCostOverTimeSetupAdjusted, WeightedCriticalRatio, WeightedCriticalRatioSetupAdjusted, WeightedHybridCrossover, WeightedHybridMutation, WeightedHybridUndoableMutation, WeightedLongestProcessingTime, WeightedShortestProcessingPlusSetupTime, WeightedShortestProcessingPlusSetupTimeLateOnly, WeightedShortestProcessingPlusSetupTimePrecompute, WeightedShortestProcessingTime, WeightedShortestProcessingTimeLateOnly, WindowLimitedBlockMoveMutation, WindowLimitedInsertionMutation, WindowLimitedReversalMutation, WindowLimitedScrambleMutation, WindowLimitedSwapMutation, WindowLimitedUndoableScrambleMutation
public interface Splittable<T extends Splittable<T>>
The Splittable interface provides multithreaded search algorithms with the ability to generate functionally identical copies of operators, and even entire metaheuristics, at the point of spawning new search threads. The state of the object that is returned may or may not be identical to that of the original. Thus, this is a distinct concept from the functionality of the Copyable interface. Additionally, the split() method is allowed to simply return the this reference, provided that it is both safe and efficient for multiple threads to share a single copy of the Splittable object.

  • Method Summary

    Modifier and Type
    Method
    Description
    T
    split()
    Generates a functionally identical copy of this object, for use in multithreaded implementations of search algorithms.

  • Method Details

    • split

      T split()
      Generates a functionally identical copy of this object, for use in multithreaded implementations of search algorithms. The state of the object that is returned may or may not be identical to that of the original. Thus, this is a distinct concept from the functionality of the Copyable interface. Classes that implement this interface must ensure that the object returned performs the same functionality, and that it does not share any state data that would be either unsafe or inefficient for concurrent access by multiple threads. The split method is allowed to simply return the this reference, provided that it is both safe and efficient for multiple threads to share a single copy of the Splittable object. The intention is to provide a multithreaded search with the capability to provide spawned threads with their own distinct search operators. Such multithreaded algorithms can call the split method for each thread it spawns to generate a functionally identical copy of the operator, but with independent state.
      Returns:
      A functionally identical copy of the object, or a reference to this if it is both safe and efficient for multiple threads to share a single instance of this Splittable object.