home | career | drupal | java | mac | mysql | perl | scala | uml | unix  

Java example source code file (UnivariateMultiStartOptimizer.java)

This example Java source code file (UnivariateMultiStartOptimizer.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

baseunivariateoptimizer, comparator, convergencechecker, deprecated, func, goaltype, notstrictlypositiveexception, nullargumentexception, randomgenerator, runtimeexception, univariatefunction, univariatemultistartoptimizer, univariatepointvaluepair, util

The UnivariateMultiStartOptimizer.java Java example source code

 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *      http://www.apache.org/licenses/LICENSE-2.0
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * See the License for the specific language governing permissions and
 * limitations under the License.

package org.apache.commons.math3.optimization.univariate;

import java.util.Arrays;
import java.util.Comparator;

import org.apache.commons.math3.analysis.UnivariateFunction;
import org.apache.commons.math3.exception.MathIllegalStateException;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NullArgumentException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.random.RandomGenerator;
import org.apache.commons.math3.optimization.GoalType;
import org.apache.commons.math3.optimization.ConvergenceChecker;

 * Special implementation of the {@link UnivariateOptimizer} 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.
 * @param <FUNC> Type of the objective function to be optimized.
 * @deprecated As of 3.1 (to be removed in 4.0).
 * @since 3.0
public class UnivariateMultiStartOptimizer<FUNC extends UnivariateFunction>
    implements BaseUnivariateOptimizer<FUNC> {
    /** Underlying classical optimizer. */
    private final BaseUnivariateOptimizer<FUNC> optimizer;
    /** Maximal number of evaluations allowed. */
    private int maxEvaluations;
    /** Number of evaluations already performed for all starts. */
    private int totalEvaluations;
    /** Number of starts to go. */
    private int starts;
    /** Random generator for multi-start. */
    private RandomGenerator generator;
    /** Found optima. */
    private UnivariatePointValuePair[] optima;

     * Create a multi-start optimizer from a single-start optimizer.
     * @param optimizer Single-start optimizer to wrap.
     * @param starts Number of starts to perform. If {@code starts == 1},
     * the {@code optimize} methods will return the same solution as
     * {@code optimizer} would.
     * @param generator Random generator to use for restarts.
     * @throws NullArgumentException if {@code optimizer} or {@code generator}
     * is {@code null}.
     * @throws NotStrictlyPositiveException if {@code starts < 1}.
    public UnivariateMultiStartOptimizer(final BaseUnivariateOptimizer<FUNC> optimizer,
                                             final int starts,
                                             final RandomGenerator generator) {
        if (optimizer == null ||
                generator == null) {
                throw new NullArgumentException();
        if (starts < 1) {
            throw new NotStrictlyPositiveException(starts);

        this.optimizer = optimizer;
        this.starts = starts;
        this.generator = generator;

     * {@inheritDoc}
    public ConvergenceChecker<UnivariatePointValuePair> getConvergenceChecker() {
        return optimizer.getConvergenceChecker();

    /** {@inheritDoc} */
    public int getMaxEvaluations() {
        return maxEvaluations;

    /** {@inheritDoc} */
    public int getEvaluations() {
        return totalEvaluations;

     * Get all the optima found during the last call to {@link
     * #optimize(int,UnivariateFunction,GoalType,double,double) optimize}.
     * The optimizer stores all the optima found during a set of
     * restarts. The {@link #optimize(int,UnivariateFunction,GoalType,double,double) 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 {@link #optimize(int,UnivariateFunction,GoalType,double,double) optimize}
     * method.
     * <br/>
     * 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 {@code null} elements
     * corresponding to the runs that did not converge. This means all
     * elements will be {@code null} if the {@link
     * #optimize(int,UnivariateFunction,GoalType,double,double) optimize}
     * method did throw an exception.
     * This also means that if the first element is not {@code null}, it is
     * the best point found across all starts.
     * @return an array containing the optima.
     * @throws MathIllegalStateException if {@link
     * #optimize(int,UnivariateFunction,GoalType,double,double) optimize}
     * has not been called.
    public UnivariatePointValuePair[] getOptima() {
        if (optima == null) {
            throw new MathIllegalStateException(LocalizedFormats.NO_OPTIMUM_COMPUTED_YET);
        return optima.clone();

    /** {@inheritDoc} */
    public UnivariatePointValuePair optimize(int maxEval, final FUNC f,
                                                 final GoalType goal,
                                                 final double min, final double max) {
        return optimize(maxEval, f, goal, min, max, min + 0.5 * (max - min));

    /** {@inheritDoc} */
    public UnivariatePointValuePair optimize(int maxEval, final FUNC f,
                                                 final GoalType goal,
                                                 final double min, final double max,
                                                 final double startValue) {
        RuntimeException lastException = null;
        optima = new UnivariatePointValuePair[starts];
        totalEvaluations = 0;

        // Multi-start loop.
        for (int i = 0; i < starts; ++i) {
            // CHECKSTYLE: stop IllegalCatch
            try {
                final double s = (i == 0) ? startValue : min + generator.nextDouble() * (max - min);
                optima[i] = optimizer.optimize(maxEval - totalEvaluations, f, goal, min, max, s);
            } catch (RuntimeException mue) {
                lastException = mue;
                optima[i] = null;
            // CHECKSTYLE: resume IllegalCatch

            totalEvaluations += optimizer.getEvaluations();


        if (optima[0] == null) {
            throw lastException; // cannot be null if starts >=1

        // Return the point with the best objective function value.
        return optima[0];

     * Sort the optima from best to worst, followed by {@code null} elements.
     * @param goal Goal type.
    private void sortPairs(final GoalType goal) {
        Arrays.sort(optima, new Comparator<UnivariatePointValuePair>() {
                /** {@inheritDoc} */
                public int compare(final UnivariatePointValuePair o1,
                                   final UnivariatePointValuePair o2) {
                    if (o1 == null) {
                        return (o2 == null) ? 0 : 1;
                    } else if (o2 == null) {
                        return -1;
                    final double v1 = o1.getValue();
                    final double v2 = o2.getValue();
                    return (goal == GoalType.MINIMIZE) ?
                        Double.compare(v1, v2) : Double.compare(v2, v1);

Other Java examples (source code examples)

Here is a short list of links related to this Java UnivariateMultiStartOptimizer.java source code file:

my book on functional programming


new blog posts


Copyright 1998-2021 Alvin Alexander, alvinalexander.com
All Rights Reserved.

A percentage of advertising revenue from
pages under the /java/jwarehouse URI on this website is
paid back to open source projects.