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Java example source code file (MultiStartMultivariateOptimizer.java)

This example Java source code file (MultiStartMultivariateOptimizer.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.

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Java - Java tags/keywords

arraylist, basemultistartmultivariateoptimizer, comparator, list, multistartmultivariateoptimizer, multivariateoptimizer, notstrictlypositiveexception, nullargumentexception, override, pointvaluepair, randomvectorgenerator, util

The MultiStartMultivariateOptimizer.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.optim.nonlinear.scalar;

import java.util.Collections;
import java.util.List;
import java.util.ArrayList;
import java.util.Comparator;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NullArgumentException;
import org.apache.commons.math3.random.RandomVectorGenerator;
import org.apache.commons.math3.optim.BaseMultiStartMultivariateOptimizer;
import org.apache.commons.math3.optim.PointValuePair;

 * Multi-start optimizer.
 * This class wraps an optimizer in order to use it several times in
 * turn with different starting points (trying to avoid being trapped
 * in a local extremum when looking for a global one).
 * @since 3.0
public class MultiStartMultivariateOptimizer
    extends BaseMultiStartMultivariateOptimizer<PointValuePair> {
    /** Underlying optimizer. */
    private final MultivariateOptimizer optimizer;
    /** Found optima. */
    private final List<PointValuePair> optima = new ArrayList();

     * 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 result will be same as if {@code optimizer}
     * is called directly.
     * @param generator Random vector generator to use for restarts.
     * @throws NullArgumentException if {@code optimizer} or {@code generator}
     * is {@code null}.
     * @throws NotStrictlyPositiveException if {@code starts < 1}.
    public MultiStartMultivariateOptimizer(final MultivariateOptimizer optimizer,
                                           final int starts,
                                           final RandomVectorGenerator generator)
        throws NullArgumentException,
        NotStrictlyPositiveException {
        super(optimizer, starts, generator);
        this.optimizer = optimizer;

     * {@inheritDoc}
    public PointValuePair[] getOptima() {
        Collections.sort(optima, getPairComparator());
        return optima.toArray(new PointValuePair[0]);

     * {@inheritDoc}
    protected void store(PointValuePair optimum) {

     * {@inheritDoc}
    protected void clear() {

     * @return a comparator for sorting the optima.
    private Comparator<PointValuePair> getPairComparator() {
        return new Comparator<PointValuePair>() {
            /** {@inheritDoc} */
            public int compare(final PointValuePair o1,
                               final PointValuePair 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 (optimizer.getGoalType() == GoalType.MINIMIZE) ?
                    Double.compare(v1, v2) : Double.compare(v2, v1);

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