org.apache.commons.math.optimization
Interface DifferentiableMultivariateRealOptimizer

All Known Implementing Classes:

AbstractScalarDifferentiableOptimizer, MultiStartDifferentiableMultivariateRealOptimizer, NonLinearConjugateGradientOptimizer, PowellOptimizer

public interface DifferentiableMultivariateRealOptimizer

This interface represents an optimization algorithm for scalar differentiable objective functions. Optimization algorithms find the input point set that either maximize or minimize an objective function.

Since:

2.0

Version:

$Revision: 1065484 $ $Date: 2011-01-31 06:45:14 +0100 (lun. 31 janv. 2011) $

See Also:

MultivariateRealOptimizer, DifferentiableMultivariateVectorialOptimizer

Method Summary

RealConvergenceChecker	getConvergenceChecker() Get the convergence checker.
int	getEvaluations() Get the number of evaluations of the objective function.
int	getGradientEvaluations() Get the number of evaluations of the objective function gradient.
int	getIterations() Get the number of iterations realized by the algorithm.
int	getMaxEvaluations() Get the maximal number of functions evaluations.
int	getMaxIterations() Get the maximal number of iterations of the algorithm.
RealPointValuePair	optimize(DifferentiableMultivariateRealFunction f, GoalType goalType, double[] startPoint) Optimizes an objective function.
void	setConvergenceChecker(RealConvergenceChecker 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.

Method Detail

setMaxIterations

void setMaxIterations(int maxIterations)

Set the maximal number of iterations of the algorithm.

Parameters:

maxIterations - maximal number of function calls

getMaxIterations

int getMaxIterations()

Get the maximal number of iterations of the algorithm.

Returns:

maximal number of iterations

getIterations

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.

Returns:

number of iterations

setMaxEvaluations

void setMaxEvaluations(int maxEvaluations)

Set the maximal number of functions evaluations.

Parameters:

maxEvaluations - maximal number of function evaluations

getMaxEvaluations

int getMaxEvaluations()

Get the maximal number of functions evaluations.

Returns:

maximal number of functions evaluations

getEvaluations

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.

Returns:

number of evaluations of the objective function

getGradientEvaluations

int getGradientEvaluations()

Get the number of evaluations of the objective function gradient.

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

Returns:

number of evaluations of the objective function gradient

setConvergenceChecker

void setConvergenceChecker(RealConvergenceChecker checker)

Set the convergence checker.

Parameters:

checker - object to use to check for convergence

getConvergenceChecker

RealConvergenceChecker getConvergenceChecker()

Get the convergence checker.

Returns:

object used to check for convergence

optimize

RealPointValuePair optimize(DifferentiableMultivariateRealFunction f,
                            GoalType goalType,
                            double[] startPoint)
                            throws FunctionEvaluationException,
                                   OptimizationException,
                                   IllegalArgumentException

Optimizes an objective function.

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

IllegalArgumentException - if the start point dimension is wrong