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Licensed to the Apache Software Foundation (ASF) under one or more
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contributor license agreements. See the NOTICE file distributed with
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this work for additional information regarding copyright ownership.
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The ASF licenses this file to You under the Apache License, Version 2.0
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(the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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<!-- $Revision: 758074 $ -->
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This package provides common interfaces for the optimization algorithms
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provided in sub-packages. The main interfaces defines optimizers and convergence
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checkers. The functions that are optimized by the algorithms provided by this
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package and its sub-packages are a subset of the one defined in the <code>analysis</code>
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package, namely the real and vector valued functions. These functions are called
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objective function here. When the goal is to minimize, the functions are often called
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cost function, this name is not used in this package.
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Optimizers are the algorithms that will either minimize or maximize, the objective function
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by changing its input variables set until an optimal set is found. There are only four
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interfaces defining the common behavior of optimizers, one for each supported type of objective
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<li>{@link org.apache.commons.math.optimization.UnivariateRealOptimizer
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UnivariateRealOptimizer} for {@link org.apache.commons.math.analysis.UnivariateRealFunction
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univariate real functions}</li>
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<li>{@link org.apache.commons.math.optimization.MultivariateRealOptimizer
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MultivariateRealOptimizer} for {@link org.apache.commons.math.analysis.MultivariateRealFunction
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multivariate real functions}</li>
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<li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
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DifferentiableMultivariateRealOptimizer} for {@link
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org.apache.commons.math.analysis.DifferentiableMultivariateRealFunction
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differentiable multivariate real functions}</li>
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<li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
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DifferentiableMultivariateVectorialOptimizer} for {@link
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org.apache.commons.math.analysis.DifferentiableMultivariateVectorialFunction
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differentiable multivariate vectorial functions}</li>
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Despite there are only four types of supported optimizers, it is possible to optimize a
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transform a {@link org.apache.commons.math.analysis.MultivariateVectorialFunction
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non-differentiable multivariate vectorial function} by converting it to a {@link
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org.apache.commons.math.analysis.MultivariateRealFunction non-differentiable multivariate
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real function} thanks to the {@link
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org.apache.commons.math.optimization.LeastSquaresConverter LeastSquaresConverter} helper class.
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The transformed function can be optimized using any implementation of the {@link
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org.apache.commons.math.optimization.MultivariateRealOptimizer MultivariateRealOptimizer} interface.
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For each of the four types of supported optimizers, there is a special implementation which
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wraps a classical optimizer in order to add it a multi-start feature. This feature call the
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underlying optimizer several times in sequence with different starting points and returns
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the best optimum found or all optima if desired. This is a classical way to prevent being
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trapped into a local extremum when looking for a global one.