org.apache.commons.math3.optimization.general

Class AbstractScalarDifferentiableOptimizer

java.lang.Object

org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>

org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer

All Implemented Interfaces:

BaseMultivariateOptimizer<DifferentiableMultivariateFunction>, BaseOptimizer<PointValuePair>, DifferentiableMultivariateOptimizer

Direct Known Subclasses:

NonLinearConjugateGradientOptimizer

Deprecated.

As of 3.1 (to be removed in 4.0).

@Deprecated
public abstract class AbstractScalarDifferentiableOptimizer
extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
implements DifferentiableMultivariateOptimizer

Base class for implementing optimizers for multivariate scalar differentiable functions. It contains boiler-plate code for dealing with gradient evaluation.

Since:

2.0

Method Summary

Modifier and Type	Method and Description
PointValuePair	optimize(int maxEval, MultivariateDifferentiableFunction f, GoalType goalType, double[] startPoint) Deprecated. Optimize an objective function.

Methods inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer

getConvergenceChecker, getEvaluations, getGoalType, getLowerBound, getMaxEvaluations, getStartPoint, getUpperBound, optimize, optimize

Methods inherited from class java.lang.Object

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

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

optimize

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

getConvergenceChecker, getEvaluations, getMaxEvaluations

Method Detail

optimize

public PointValuePair optimize(int maxEval,
                               MultivariateDifferentiableFunction f,
                               GoalType goalType,
                               double[] startPoint)

Deprecated.

Optimize an objective function.

Parameters:

f - Objective function.

goalType - Type of optimization goal: either GoalType.MAXIMIZE or GoalType.MINIMIZE.

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.