org.apache.commons.math.optimization.MultivariateRealOptimizer Maven / Gradle / Ivy
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* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.commons.math.optimization;
import org.apache.commons.math.FunctionEvaluationException;
import org.apache.commons.math.analysis.MultivariateRealFunction;
/**
* This interface represents an optimization algorithm for {@link MultivariateRealFunction
* scalar objective functions}.
* Optimization algorithms find the input point set that either {@link GoalType
* maximize or minimize} an objective function.
* @see DifferentiableMultivariateRealOptimizer
* @see DifferentiableMultivariateVectorialOptimizer
* @version $Revision: 1065481 $ $Date: 2011-01-31 06:31:41 +0100 (lun. 31 janv. 2011) $
* @since 2.0
*/
public interface MultivariateRealOptimizer {
/** Set the maximal number of iterations of the algorithm.
* @param maxIterations maximal number of algorithm iterations
*/
void setMaxIterations(int maxIterations);
/** Get the maximal number of iterations of the algorithm.
* @return maximal number of iterations
*/
int getMaxIterations();
/** Set the maximal number of functions evaluations.
* @param maxEvaluations maximal number of function evaluations
*/
void setMaxEvaluations(int maxEvaluations);
/** Get the maximal number of functions evaluations.
* @return maximal number of functions evaluations
*/
int getMaxEvaluations();
/** Get the number of iterations realized by the algorithm.
*
* The number of evaluations corresponds to the last call to the
* {@link #optimize(MultivariateRealFunction, GoalType, double[]) optimize}
* method. It is 0 if the method has not been called yet.
*
* @return number of iterations
*/
int getIterations();
/** Get the number of evaluations of the objective function.
*
* The number of evaluations corresponds to the last call to the
* {@link #optimize(MultivariateRealFunction, GoalType, double[]) optimize}
* method. It is 0 if the method has not been called yet.
*
* @return number of evaluations of the objective function
*/
int getEvaluations();
/** Set the convergence checker.
* @param checker object to use to check for convergence
*/
void setConvergenceChecker(RealConvergenceChecker checker);
/** Get the convergence checker.
* @return object used to check for convergence
*/
RealConvergenceChecker getConvergenceChecker();
/** Optimizes an objective function.
* @param f objective function
* @param goalType type of optimization goal: either {@link GoalType#MAXIMIZE}
* or {@link GoalType#MINIMIZE}
* @param startPoint the start point for optimization
* @return the point/value pair giving the optimal value for objective function
* @exception FunctionEvaluationException if the objective function throws one during
* the search
* @exception OptimizationException if the algorithm failed to converge
* @exception IllegalArgumentException if the start point dimension is wrong
*/
RealPointValuePair optimize(MultivariateRealFunction f,
GoalType goalType,
double[] startPoint)
throws FunctionEvaluationException, OptimizationException, IllegalArgumentException;
}