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Diffstat (limited to 'src/main/java/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizer.java')
| -rw-r--r-- | src/main/java/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizer.java | 216 |
1 files changed, 216 insertions, 0 deletions
diff --git a/src/main/java/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizer.java b/src/main/java/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizer.java new file mode 100644 index 0000000..fdba1d5 --- /dev/null +++ b/src/main/java/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizer.java @@ -0,0 +1,216 @@ +/* + * 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, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.commons.math.optimization; + +import java.util.Arrays; +import java.util.Comparator; + +import org.apache.commons.math.FunctionEvaluationException; +import org.apache.commons.math.MathRuntimeException; +import org.apache.commons.math.analysis.MultivariateRealFunction; +import org.apache.commons.math.exception.util.LocalizedFormats; +import org.apache.commons.math.random.RandomVectorGenerator; + +/** + * Special implementation of the {@link MultivariateRealOptimizer} interface adding + * multi-start features to an existing optimizer. + * <p> + * 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. + * </p> + * @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $ + * @since 2.0 + */ +public class MultiStartMultivariateRealOptimizer + implements MultivariateRealOptimizer { + + /** Underlying classical optimizer. */ + private final MultivariateRealOptimizer optimizer; + + /** Maximal number of iterations allowed. */ + private int maxIterations; + + /** Maximal number of evaluations allowed. */ + private int maxEvaluations; + + /** Number of iterations already performed for all starts. */ + private int totalIterations; + + /** 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 RandomVectorGenerator generator; + + /** Found optima. */ + private RealPointValuePair[] 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 (including the + * first one), multi-start is disabled if value is less than or + * equal to 1 + * @param generator random vector generator to use for restarts + */ + public MultiStartMultivariateRealOptimizer(final MultivariateRealOptimizer optimizer, + final int starts, + final RandomVectorGenerator generator) { + this.optimizer = optimizer; + this.totalIterations = 0; + this.totalEvaluations = 0; + this.starts = starts; + this.generator = generator; + this.optima = null; + setMaxIterations(Integer.MAX_VALUE); + setMaxEvaluations(Integer.MAX_VALUE); + } + + /** Get all the optima found during the last call to {@link + * #optimize(MultivariateRealFunction, GoalType, double[]) optimize}. + * <p>The optimizer stores all the optima found during a set of + * restarts. The {@link #optimize(MultivariateRealFunction, GoalType, + * 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(MultivariateRealFunction, GoalType, double[]) optimize} + * method. + * </p> + * <p> + * 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 and null elements + * corresponding to the runs that did not converge. This means all + * elements will be null if the {@link #optimize(MultivariateRealFunction, + * GoalType, double[]) optimize} method did throw a {@link + * org.apache.commons.math.ConvergenceException ConvergenceException}). + * This also means that if the first element is non null, it is the best + * point found across all starts.</p> + * @return array containing the optima + * @exception IllegalStateException if {@link #optimize(MultivariateRealFunction, + * GoalType, double[]) optimize} has not been called + */ + public RealPointValuePair[] getOptima() throws IllegalStateException { + if (optima == null) { + throw MathRuntimeException.createIllegalStateException(LocalizedFormats.NO_OPTIMUM_COMPUTED_YET); + } + return optima.clone(); + } + + /** {@inheritDoc} */ + public void setMaxIterations(int maxIterations) { + this.maxIterations = maxIterations; + } + + /** {@inheritDoc} */ + public int getMaxIterations() { + return maxIterations; + } + + /** {@inheritDoc} */ + public void setMaxEvaluations(int maxEvaluations) { + this.maxEvaluations = maxEvaluations; + } + + /** {@inheritDoc} */ + public int getMaxEvaluations() { + return maxEvaluations; + } + + /** {@inheritDoc} */ + public int getIterations() { + return totalIterations; + } + + /** {@inheritDoc} */ + public int getEvaluations() { + return totalEvaluations; + } + + /** {@inheritDoc} */ + public void setConvergenceChecker(RealConvergenceChecker checker) { + optimizer.setConvergenceChecker(checker); + } + + /** {@inheritDoc} */ + public RealConvergenceChecker getConvergenceChecker() { + return optimizer.getConvergenceChecker(); + } + + /** {@inheritDoc} */ + public RealPointValuePair optimize(final MultivariateRealFunction f, + final GoalType goalType, + double[] startPoint) + throws FunctionEvaluationException, OptimizationException, FunctionEvaluationException { + + optima = new RealPointValuePair[starts]; + totalIterations = 0; + totalEvaluations = 0; + + // multi-start loop + for (int i = 0; i < starts; ++i) { + + try { + optimizer.setMaxIterations(maxIterations - totalIterations); + optimizer.setMaxEvaluations(maxEvaluations - totalEvaluations); + optima[i] = optimizer.optimize(f, goalType, + (i == 0) ? startPoint : generator.nextVector()); + } catch (FunctionEvaluationException fee) { + optima[i] = null; + } catch (OptimizationException oe) { + optima[i] = null; + } + + totalIterations += optimizer.getIterations(); + totalEvaluations += optimizer.getEvaluations(); + + } + + // sort the optima from best to worst, followed by null elements + Arrays.sort(optima, new Comparator<RealPointValuePair>() { + public int compare(final RealPointValuePair o1, final RealPointValuePair 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 (goalType == GoalType.MINIMIZE) ? + Double.compare(v1, v2) : Double.compare(v2, v1); + } + }); + + if (optima[0] == null) { + throw new OptimizationException( + LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT, + starts); + } + + // return the found point given the best objective function value + return optima[0]; + + } + +} |