Package org.hipparchus.optim.univariate

Class MultiStartUnivariateOptimizer

java.lang.Object
org.hipparchus.optim.BaseOptimizer<UnivariatePointValuePair>
org.hipparchus.optim.univariate.UnivariateOptimizer
org.hipparchus.optim.univariate.MultiStartUnivariateOptimizer
public class MultiStartUnivariateOptimizer extends UnivariateOptimizer
Special implementation of the UnivariateOptimizer interface adding multi-start features to an existing optimizer.
This class wraps an optimizer in order to use it several times in turn with different starting points (trying to avoid being trapped in a local extremum when looking for a global one).

  • Constructor Details

    • MultiStartUnivariateOptimizer

      public MultiStartUnivariateOptimizer(UnivariateOptimizer optimizer, int starts, RandomGenerator generator)
      Create a multi-start optimizer from a single-start optimizer.
      Parameters:
      optimizer - Single-start optimizer to wrap.
      starts - Number of starts to perform. If starts == 1, the optimize methods will return the same solution as optimizer would.
      generator - Random generator to use for restarts.
      Throws:
      MathIllegalArgumentException - if starts < 1.

  • Method Details

    • getEvaluations

      public int getEvaluations()
      Gets 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.
      Overrides:
      getEvaluations in class BaseOptimizer<UnivariatePointValuePair>
      Returns:
      the number of evaluations of the objective function.

    • getOptima

      public UnivariatePointValuePair[] getOptima()
      Gets 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 null elements corresponding to the runs that did not converge. This means all elements will be null if the optimize method did throw an exception. This also means that if the first element is not null, it is the best point found across all starts.
      Returns:
      an array containing the optima.
      Throws:
      MathIllegalStateException - if optimize has not been called.

    • optimize

      public UnivariatePointValuePair optimize(OptimizationData... optData)
      Stores data and performs the optimization.

      The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.

      When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).

      Important note: Subclasses must override BaseOptimizer.parseOptimizationData(OptimizationData[]) if they need to register their own options; but then, they must also call super.parseOptimizationData(optData) within that method.

      Overrides:
      optimize in class UnivariateOptimizer
      Parameters:
      optData - Optimization data. In addition to those documented in BaseOptimizer, this method will register the following data:
      Returns:
      a point/value pair that satisfies the convergence criteria.
      Throws:
      MathIllegalStateException - if optData does not contain an instance of MaxEval or SearchInterval.

    • doOptimize

      protected UnivariatePointValuePair doOptimize()
      Performs the bulk of the optimization algorithm.
      Specified by:
      doOptimize in class BaseOptimizer<UnivariatePointValuePair>
      Returns:
      the point/value pair giving the optimal value of the objective function.