Uses of Interface
org.cicirello.search.sa.AnnealingSchedule
Package
Description
This package includes classes and interfaces directly related to implementing simulated
annealing.
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Uses of AnnealingSchedule in org.cicirello.search.sa
Modifier and TypeClassDescriptionfinal class
An AcceptanceTracker can be used to extract fine-grained information about the behavior of an annealing schedule across several runs of simulated annealing.final class
This class implements the classic and most commonly encountered cooling schedule for simulated annealing, the annealing schedule known as exponential cooling (sometimes referred to as geometric cooling).final class
This class implements the linear cooling schedule for simulated annealing.final class
This class implements logarithmic cooling, a classic annealing schedule.final class
This class implements an optimized variant of the Modified Lam annealing schedule.final class
This class implements the Modified Lam annealing schedule, which dynamically adjusts simulated annealing's temperature parameter up and down to either decrease or increase the neighbor acceptance rate as necessary to attempt to match a theoretically determined ideal.final class
This class implements a parameter-free version of the classic cooling schedule for simulated annealing known as exponential cooling (sometimes referred to as geometric cooling).final class
This class implements a parameter-free version of the linear cooling schedule for simulated annealing.final class
This class implements the Self-Tuning Lam annealing schedule, which is an improved variation of the Modified Lam annealing schedule.ModifierConstructorDescriptionAcceptanceTracker
(AnnealingSchedule schedule) Constructs the AcceptanceTracker.SimulatedAnnealing
(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal) Creates a SimulatedAnnealing search instance for integer-valued optimization problems.SimulatedAnnealing
(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, ProgressTracker<T> tracker) Creates a SimulatedAnnealing search instance for integer-valued optimization problems.SimulatedAnnealing
(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, ProgressTracker<T> tracker, SimpleLocalMetaheuristic<T> hc) Creates a SimulatedAnnealing search instance for integer-valued optimization problems that runs a hill climber as a post-processing step.SimulatedAnnealing
(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, SimpleLocalMetaheuristic<T> hc) Creates a SimulatedAnnealing search instance for integer-valued optimization problems that runs a hill climber as a post-processing step.SimulatedAnnealing
(OptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal) Creates a SimulatedAnnealing search instance for real-valued optimization problems.SimulatedAnnealing
(OptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, ProgressTracker<T> tracker) Creates a SimulatedAnnealing search instance for real-valued optimization problems.SimulatedAnnealing
(OptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, ProgressTracker<T> tracker, SimpleLocalMetaheuristic<T> hc) Creates a SimulatedAnnealing search instance for real-valued optimization problems that runs a hill climber as a post-processing step.SimulatedAnnealing
(OptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, SimpleLocalMetaheuristic<T> hc) Creates a SimulatedAnnealing search instance for real-valued optimization problems that runs a hill climber as a post-processing step.