/*
 * 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.
 */

/**
 * Generally, optimizers are algorithms that will either {@link
 * org.apache.commons.math3.optim.nonlinear.scalar.GoalType#MINIMIZE minimize} or {@link
 * org.apache.commons.math3.optim.nonlinear.scalar.GoalType#MAXIMIZE maximize} a scalar function,
 * called the {@link org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction <em>objective
 * function</em>}. <br>
 * For some scalar objective functions the gradient can be computed (analytically or numerically).
 * Algorithms that use this knowledge are defined in the {@link
 * org.apache.commons.math3.optim.nonlinear.scalar.gradient} package. The algorithms that do not
 * need this additional information are located in the {@link
 * org.apache.commons.math3.optim.nonlinear.scalar.noderiv} package.
 *
 * <p>Some problems are solved more efficiently by algorithms that, instead of an objective
 * function, need access to a {@link org.apache.commons.math3.optim.nonlinear.vector.ModelFunction
 * <em>model function</em>}: such a model predicts a set of values which the algorithm tries to
 * match with a set of given {@link org.apache.commons.math3.optim.nonlinear.vector.Target target
 * values}. Those algorithms are located in the {@link
 * org.apache.commons.math3.optim.nonlinear.vector} package. <br>
 * Algorithms that also require the {@link
 * org.apache.commons.math3.optim.nonlinear.vector.ModelFunctionJacobian Jacobian matrix of the
 * model} are located in the {@link org.apache.commons.math3.optim.nonlinear.vector.jacobian}
 * package. <br>
 * The {@link org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
 * non-linear least-squares optimizers} are a specialization of the the latter, that minimize the
 * distance (called <em>cost</em> or <em>&chi;<sup>2</sup></em>) between model and observations.
 * <br>
 * For cases where the Jacobian cannot be provided, a utility class will {@link
 * org.apache.commons.math3.optim.nonlinear.scalar.LeastSquaresConverter convert} a (vector) model
 * into a (scalar) objective function.
 *
 * <p>This package provides common functionality for the optimization algorithms. Abstract classes
 * ({@link org.apache.commons.math3.optim.BaseOptimizer} and {@link
 * org.apache.commons.math3.optim.BaseMultivariateOptimizer}) contain boiler-plate code for storing
 * {@link org.apache.commons.math3.optim.MaxEval evaluations} and {@link
 * org.apache.commons.math3.optim.MaxIter iterations} counters and a user-defined {@link
 * org.apache.commons.math3.optim.ConvergenceChecker convergence checker}.
 *
 * <p>For each of the optimizer types, there is a special implementation that wraps an optimizer
 * instance and provides a "multi-start" feature: it calls the underlying optimizer several times
 * with different starting points and returns the best optimum found, or all optima if so desired.
 * This could be useful to avoid being trapped in a local extremum.
 */
package org.apache.commons.math3.optim;