org.apache.commons.math3.optimization
Interface BaseMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>

Type Parameters:

FUNC - Type of the objective function to be optimized.

All Superinterfaces:

BaseOptimizer<PointVectorValuePair>

All Known Subinterfaces:

DifferentiableMultivariateVectorOptimizer, MultivariateDifferentiableVectorOptimizer

All Known Implementing Classes:

AbstractLeastSquaresOptimizer, BaseAbstractMultivariateVectorOptimizer, BaseMultivariateVectorMultiStartOptimizer, DifferentiableMultivariateVectorMultiStartOptimizer, GaussNewtonOptimizer, LevenbergMarquardtOptimizer, MultivariateDifferentiableVectorMultiStartOptimizer

Deprecated. As of 3.1 (to be removed in 4.0).

@Deprecated
public interface BaseMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>
extends BaseOptimizer<PointVectorValuePair>

This interface is mainly intended to enforce the internal coherence of Commons-Math. Users of the API are advised to base their code on the following interfaces:

• DifferentiableMultivariateVectorOptimizer

Since:

3.0

Version:

$Id: BaseMultivariateVectorOptimizer.java 7721 2013-02-14 14:07:13Z CardosoP $

Method Summary

PointVectorValuePair

optimize(int maxEval, FUNC f, double[] target, double[] weight, double[] startPoint) Deprecated. As of 3.1. In 4.0, this will be replaced by the declaration corresponding to this method.

Methods inherited from interface org.apache.commons.math3.optimization.BaseOptimizer

getConvergenceChecker, getEvaluations, getMaxEvaluations

Method Detail

optimize

@Deprecated
PointVectorValuePair optimize(int maxEval,
                                         FUNC f,
                                         double[] target,
                                         double[] weight,
                                         double[] startPoint)

Deprecated. As of 3.1. In 4.0, this will be replaced by the declaration corresponding to this method.

Optimize an objective function. Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weighti(objectivei - targeti)2

Parameters:

f - Objective function.

target - Target value for the objective functions at optimum.

weight - Weights for the least squares cost computation.

startPoint - Start point for optimization.

maxEval - Maximum number of function evaluations.

Returns:

the point/value pair giving the optimal value for objective function.

Throws:

DimensionMismatchException - if the start point dimension is wrong.

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.

NullArgumentException - if any argument is null.