Class MultiStartMultivariateRealOptimizer

java.lang.Object
org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
All Implemented Interfaces:
MultivariateRealOptimizer

public class MultiStartMultivariateRealOptimizer extends 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 Details

    • 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 Details

    • getOptima

      public RealPointValuePair[] getOptima() throws 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:
      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
    • setConvergenceChecker

      public void setConvergenceChecker(RealConvergenceChecker checker)
      Set the convergence checker.
      Specified by:
      setConvergenceChecker in interface MultivariateRealOptimizer
      Parameters:
      checker - object to use to check for convergence
    • getConvergenceChecker

      public RealConvergenceChecker getConvergenceChecker()
      Get the convergence checker.
      Specified by:
      getConvergenceChecker in interface MultivariateRealOptimizer
      Returns:
      object used to check for convergence
    • optimize

      Optimizes an objective function.
      Specified by:
      optimize in interface MultivariateRealOptimizer
      Parameters:
      f - objective function
      goalType - type of optimization goal: either GoalType.MAXIMIZE or GoalType.MINIMIZE
      startPoint - the start point for optimization
      Returns:
      the point/value pair giving the optimal value for objective function
      Throws:
      FunctionEvaluationException - if the objective function throws one during the search
      OptimizationException - if the algorithm failed to converge