Package org.apache.commons.math.optimization

Class MultiStartDifferentiableMultivariateVectorialOptimizer

java.lang.Object

org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer

All Implemented Interfaces:

DifferentiableMultivariateVectorialOptimizer

public class MultiStartDifferentiableMultivariateVectorialOptimizer
extends Object
implements DifferentiableMultivariateVectorialOptimizer

Special implementation of the DifferentiableMultivariateVectorialOptimizer 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

Constructor Summary

Constructors

Constructor	Description
MultiStartDifferentiableMultivariateVectorialOptimizer(DifferentiableMultivariateVectorialOptimizer optimizer, int starts, RandomVectorGenerator generator)	Create a multi-start optimizer from a single-start optimizer

Method Summary

Modifier and Type	Method	Description
VectorialConvergenceChecker	getConvergenceChecker()	Get the convergence checker.
int	getEvaluations()	Get the number of evaluations of the objective function.
int	getIterations()	Get the number of iterations realized by the algorithm.
int	getJacobianEvaluations()	Get the number of evaluations of the objective function jacobian .
int	getMaxEvaluations()	Get the maximal number of functions evaluations.
int	getMaxIterations()	Get the maximal number of iterations of the algorithm.
VectorialPointValuePair[]	getOptima()	Get all the optima found during the last call to optimize.
VectorialPointValuePair	optimize(DifferentiableMultivariateVectorialFunction f, double[] target, double[] weights, double[] startPoint)	Optimizes an objective function.
void	setConvergenceChecker(VectorialConvergenceChecker checker)	Set the convergence checker.
void	setMaxEvaluations(int maxEvaluations)	Set the maximal number of functions evaluations.
void	setMaxIterations(int maxIterations)	Set the maximal number of iterations of the algorithm.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

MultiStartDifferentiableMultivariateVectorialOptimizer

public MultiStartDifferentiableMultivariateVectorialOptimizer(DifferentiableMultivariateVectorialOptimizer 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 VectorialPointValuePair[] 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 DifferentiableMultivariateVectorialOptimizer

Parameters:

maxIterations - maximal number of function calls .

getMaxIterations

public int getMaxIterations()

Get the maximal number of iterations of the algorithm.

Specified by:

getMaxIterations in interface DifferentiableMultivariateVectorialOptimizer

Returns:

maximal number of iterations

getIterations

public int getIterations()

Get the number of iterations realized by the algorithm.

Specified by:

getIterations in interface DifferentiableMultivariateVectorialOptimizer

Returns:

number of iterations

setMaxEvaluations

public void setMaxEvaluations(int maxEvaluations)

Set the maximal number of functions evaluations.

Specified by:

setMaxEvaluations in interface DifferentiableMultivariateVectorialOptimizer

Parameters:

maxEvaluations - maximal number of function evaluations

getMaxEvaluations

public int getMaxEvaluations()

Get the maximal number of functions evaluations.

Specified by:

getMaxEvaluations in interface DifferentiableMultivariateVectorialOptimizer

Returns:

maximal number of functions evaluations

getEvaluations

public int getEvaluations()

Get the number of evaluations of the objective function.

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

Specified by:

getEvaluations in interface DifferentiableMultivariateVectorialOptimizer

Returns:

number of evaluations of the objective function

getJacobianEvaluations

public int getJacobianEvaluations()

Get the number of evaluations of the objective function jacobian .

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

Specified by:

getJacobianEvaluations in interface DifferentiableMultivariateVectorialOptimizer

Returns:

number of evaluations of the objective function jacobian

setConvergenceChecker

public void setConvergenceChecker(VectorialConvergenceChecker checker)

Set the convergence checker.

Specified by:

setConvergenceChecker in interface DifferentiableMultivariateVectorialOptimizer

Parameters:

checker - object to use to check for convergence

getConvergenceChecker

public VectorialConvergenceChecker getConvergenceChecker()

Get the convergence checker.

Specified by:

getConvergenceChecker in interface DifferentiableMultivariateVectorialOptimizer

Returns:

object used to check for convergence

optimize

public VectorialPointValuePair optimize(DifferentiableMultivariateVectorialFunction f,
                                        double[] target,
                                        double[] weights,
                                        double[] startPoint)
                                 throws FunctionEvaluationException,
                                        OptimizationException,
                                        IllegalArgumentException

Optimizes an objective function.

Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weight_i(objective_i-target_i)²

Specified by:

optimize in interface DifferentiableMultivariateVectorialOptimizer

Parameters:

f - objective function

target - target value for the objective functions at optimum

weights - weight for the least squares cost computation

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

IllegalArgumentException - if the start point dimension is wrong