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

Interface ReoptimizableMetaheuristic<T extends Copyable<T>>

Type Parameters:
T - The type of object under optimization.
All Superinterfaces:
Metaheuristic<T>, Splittable<TrackableSearch<T>>, TrackableSearch<T>
All Known Subinterfaces:
SingleSolutionMetaheuristic<T>
All Known Implementing Classes:
AdaptiveEvolutionaryAlgorithm, AdaptiveMutationOnlyEvolutionaryAlgorithm, GenerationalEvolutionaryAlgorithm, GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators, GenerationalMutationOnlyEvolutionaryAlgorithm, GeneticAlgorithm, MutationOnlyGeneticAlgorithm, NaiveGenerationalEvolutionaryAlgorithm, OnePlusOneEvolutionaryAlgorithm, OnePlusOneGeneticAlgorithm, ParallelReoptimizableMetaheuristic, ParallelReoptimizableMultistarter, ReoptimizableMultistarter, SimpleGeneticAlgorithm, SimulatedAnnealing, TimedParallelReoptimizableMultistarter
public interface ReoptimizableMetaheuristic<T extends Copyable<T>> extends Metaheuristic<T>
This interface defines the required methods for implementations of metaheuristics, for which the maximum run length can be specified, and which have the capability of restarting from a previously optimized solution.

  • Method Details

    • reoptimize

      SolutionCostPair<T> reoptimize(int runLength)
      Executes a run of the metaheuristic beginning at the previously best found solution rather than from a random one. If the metaheuristic had not been previously run, then this method will start from a randomly generated solution. This method does reinitialize control parameters of the metaheuristic that may have changed during the previous calls to optimize or reoptimize.

      Implementing classes should provide more specific documentation of this method to define in particular what run length means in the context of the given metaheuristic. It is also recommended that implementing classes rename the parameter to be a more meaningful name within the context of that metaheuristic.

      Parameters:
      runLength - The length of a run of this metaheuristic.
      Returns:
      The current solution at the end of this run and its cost, which may or may not be the best of run solution, and which may or may not be the same as the solution contained in this metaheuristic's ProgressTracker, which contains the best of all runs. Returns null if the run did not execute, such as if the ProgressTracker already contains the theoretical best solution.

    • split

      ReoptimizableMetaheuristic<T> split()
      Description copied from interface: Splittable
      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.
      Specified by:
      split in interface Metaheuristic<T extends Copyable<T>>
      Specified by:
      split in interface Splittable<T extends Copyable<T>>
      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.