Class IterativeSampling<T extends Copyable<T>>

  • Type Parameters:
    T - The type of object under optimization.
    All Implemented Interfaces:
    Splittable<TrackableSearch<T>>, Metaheuristic<T>, SimpleMetaheuristic<T>, TrackableSearch<T>

    public final class IterativeSampling<T extends Copyable<T>>
    extends Object

    Iterative sampling is the simplest possible form of a stochastic sampling search. In iterative sampling, the search generates N random candidate solutions to the problem, each sampled uniformly at random from the space of possible solutions. It evaluates each of the N candidate solutions with respect to the optimization problem's cost function, and returns the best of the N candidate solutions.

    For an early empirical comparison of iterative sampling with systematic search algorithms, see:
    P. Langley. Systematic and nonsystematic search strategies. Proceedings of the First International Conference on Artificial Intelligence Planning Systems, pages 145–152, 1992.

    • Constructor Detail

      • IterativeSampling

        public IterativeSampling​(OptimizationProblem<T> problem,
                                 Initializer<T> initializer,
                                 ProgressTracker<T> tracker)
        Constructs an iterative sampling search for a real-valued optimization problem.
        Parameters:
        problem - An instance of an optimization problem to solve.
        initializer - The source of random solutions.
        tracker - A ProgressTracker object, which is used to keep track of the best solution found during the run, the time when it was found, and other related data.
        Throws:
        NullPointerException - if any of the parameters are null.
      • IterativeSampling

        public IterativeSampling​(IntegerCostOptimizationProblem<T> problem,
                                 Initializer<T> initializer,
                                 ProgressTracker<T> tracker)
        Constructs an iterative sampling search for a integer-valued optimization problem.
        Parameters:
        problem - An instance of an optimization problem to solve.
        initializer - The source of random solutions.
        tracker - A ProgressTracker object, which is used to keep track of the best solution found during the run, the time when it was found, and other related data.
        Throws:
        NullPointerException - if any of the parameters are null.
      • IterativeSampling

        public IterativeSampling​(OptimizationProblem<T> problem,
                                 Initializer<T> initializer)
        Constructs an iterative sampling search for a real-valued optimization problem. A ProgressTracker is created for you.
        Parameters:
        problem - An instance of an optimization problem to solve.
        initializer - The source of random solutions.
        Throws:
        NullPointerException - if any of the parameters are null.
      • IterativeSampling

        public IterativeSampling​(IntegerCostOptimizationProblem<T> problem,
                                 Initializer<T> initializer)
        Constructs an iterative sampling search for a integer-valued optimization problem. A ProgressTracker is created for you.
        Parameters:
        problem - An instance of an optimization problem to solve.
        initializer - The source of random solutions.
        Throws:
        NullPointerException - if any of the parameters are null.
    • Method Detail

      • split

        public IterativeSampling<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 SimpleMetaheuristic<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.
      • optimize

        public final SolutionCostPair<T> optimize()
        Description copied from interface: SimpleMetaheuristic

        Executes a single run of a metaheuristic whose run length cannot be specified (e.g., a hill climber that terminates when it reaches a local optima, or a stochastic sampler that terminates when it constructs one solution, etc). If this method is called multiple times, each call is randomized in some algorithm dependent way (e.g., a hill climber begins at a new randomly generated starting solution), and reinitializes any control parameters that may have changed during the previous call to optimize to the start of run state.

        Specified by:
        optimize in interface SimpleMetaheuristic<T extends Copyable<T>>
        Returns:
        The current solution at the end of this run and its cost, 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.
      • optimize

        public final SolutionCostPair<T> optimize​(int numSamples)

        Generates multiple stochastic heuristic samples. Returns the best solution of the set of samples.

        Specified by:
        optimize in interface Metaheuristic<T extends Copyable<T>>
        Parameters:
        numSamples - The number of samples to perform.
        Returns:
        The best solution of this set of samples, which may or may not be the same as the solution contained in this search's ProgressTracker, which contains the best of all runs across all calls to the various optimize methods. Returns null if no runs executed, such as if the ProgressTracker already contains the theoretical best solution.
      • getProgressTracker

        public final ProgressTracker<T> getProgressTracker()
        Description copied from interface: TrackableSearch
        Gets the ProgressTracker object that is in use for tracking search progress. The object returned by this method contains the best solution found during the search (including across multiple concurrent runs if the search is multithreaded, or across multiple restarts if the run methods were called multiple times), as well as cost of that solution, among other information. See the ProgressTracker documentation for more information about the search data tracked by this object.
        Specified by:
        getProgressTracker in interface TrackableSearch<T extends Copyable<T>>
        Returns:
        the ProgressTracker in use by this metaheuristic.
      • setProgressTracker

        public final void setProgressTracker​(ProgressTracker<T> tracker)
        Description copied from interface: TrackableSearch
        Sets the ProgressTracker object that is in use for tracking search progress. Any previously set ProgressTracker is replaced by this one.
        Specified by:
        setProgressTracker in interface TrackableSearch<T extends Copyable<T>>
        Parameters:
        tracker - The new ProgressTracker to set. The tracker must not be null. This method does nothing if tracker is null.
      • getTotalRunLength

        public final long getTotalRunLength()
        Description copied from interface: TrackableSearch

        Gets the total run length of the metaheuristic. This is the total run length across all calls to the search. This may differ from what may be expected based on run lengths. For example, the search terminates if it finds the theoretical best solution, and also immediately returns if a prior call found the theoretical best. In such cases, the total run length may be less than the requested run length.

        The meaning of run length may vary from one metaheuristic to another. Therefore, implementing classes should provide fresh documentation rather than relying entirely on the interface documentation.

        Specified by:
        getTotalRunLength in interface TrackableSearch<T extends Copyable<T>>
        Returns:
        the total run length of the metaheuristic
      • getProblem

        public final Problem<T> getProblem()
        Description copied from interface: TrackableSearch
        Gets a reference to the problem that this search is solving.
        Specified by:
        getProblem in interface TrackableSearch<T extends Copyable<T>>
        Returns:
        a reference to the problem.