Class MultiStartMultivariateRealOptimizer

  • All Implemented Interfaces:
    MultivariateRealOptimizer

    public class MultiStartMultivariateRealOptimizer
    extends java.lang.Object
    implements MultivariateRealOptimizer
    Special implementation of the MultivariateRealOptimizer interface adding multi-start features to an existing optimizer.

    This class wraps a classical optimizer to use it several times in turn with different starting points in order to avoid being trapped into a local extremum when looking for a global one.

    Since:
    2.0
    Version:
    $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $
    • Constructor Detail

      • MultiStartMultivariateRealOptimizer

        public MultiStartMultivariateRealOptimizer​(MultivariateRealOptimizer optimizer,
                                                   int starts,
                                                   RandomVectorGenerator generator)
        Create a multi-start optimizer from a single-start optimizer
        Parameters:
        optimizer - single-start optimizer to wrap
        starts - number of starts to perform (including the first one), multi-start is disabled if value is less than or equal to 1
        generator - random vector generator to use for restarts
    • Method Detail

      • getOptima

        public RealPointValuePair[] getOptima()
                                       throws java.lang.IllegalStateException
        Get all the optima found during the last call to optimize.

        The optimizer stores all the optima found during a set of restarts. The optimize method returns the best point only. This method returns all the points found at the end of each starts, including the best one already returned by the optimize method.

        The returned array as one element for each start as specified in the constructor. It is ordered with the results from the runs that did converge first, sorted from best to worst objective value (i.e in ascending order if minimizing and in descending order if maximizing), followed by and null elements corresponding to the runs that did not converge. This means all elements will be null if the optimize method did throw a ConvergenceException). This also means that if the first element is non null, it is the best point found across all starts.

        Returns:
        array containing the optima
        Throws:
        java.lang.IllegalStateException - if optimize has not been called
      • setMaxIterations

        public void setMaxIterations​(int maxIterations)
        Set the maximal number of iterations of the algorithm.
        Specified by:
        setMaxIterations in interface MultivariateRealOptimizer
        Parameters:
        maxIterations - maximal number of algorithm iterations
      • getMaxIterations

        public int getMaxIterations()
        Get the maximal number of iterations of the algorithm.
        Specified by:
        getMaxIterations in interface MultivariateRealOptimizer
        Returns:
        maximal number of iterations
      • setMaxEvaluations

        public void setMaxEvaluations​(int maxEvaluations)
        Set the maximal number of functions evaluations.
        Specified by:
        setMaxEvaluations in interface MultivariateRealOptimizer
        Parameters:
        maxEvaluations - maximal number of function evaluations
      • getMaxEvaluations

        public int getMaxEvaluations()
        Get the maximal number of functions evaluations.
        Specified by:
        getMaxEvaluations in interface MultivariateRealOptimizer
        Returns:
        maximal number of functions evaluations
      • getIterations

        public int getIterations()
        Get the number of iterations realized by the algorithm.

        The number of evaluations corresponds to the last call to the optimize method. It is 0 if the method has not been called yet.

        Specified by:
        getIterations in interface MultivariateRealOptimizer
        Returns:
        number of iterations
      • getEvaluations

        public int getEvaluations()
        Get the number of evaluations of the objective function.

        The number of evaluations corresponds to the last call to the optimize method. It is 0 if the method has not been called yet.

        Specified by:
        getEvaluations in interface MultivariateRealOptimizer
        Returns:
        number of evaluations of the objective function