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The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.

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/*
 * 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.math3.optimization.linear;

import java.util.Collection;
import java.util.Collections;

import org.apache.commons.math3.exception.MathIllegalStateException;
import org.apache.commons.math3.exception.MaxCountExceededException;
import org.apache.commons.math3.optimization.GoalType;
import org.apache.commons.math3.optimization.PointValuePair;

/**
 * Base class for implementing linear optimizers.
 * 

* This base class handles the boilerplate methods associated to thresholds * settings and iterations counters. * * @deprecated As of 3.1 (to be removed in 4.0). * @since 2.0 */ @Deprecated public abstract class AbstractLinearOptimizer implements LinearOptimizer { /** Default maximal number of iterations allowed. */ public static final int DEFAULT_MAX_ITERATIONS = 100; /** * Linear objective function. * @since 2.1 */ private LinearObjectiveFunction function; /** * Linear constraints. * @since 2.1 */ private Collection linearConstraints; /** * Type of optimization goal: either {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}. * @since 2.1 */ private GoalType goal; /** * Whether to restrict the variables to non-negative values. * @since 2.1 */ private boolean nonNegative; /** Maximal number of iterations allowed. */ private int maxIterations; /** Number of iterations already performed. */ private int iterations; /** * Simple constructor with default settings. *

The maximal number of evaluation is set to its default value.

*/ protected AbstractLinearOptimizer() { setMaxIterations(DEFAULT_MAX_ITERATIONS); } /** * @return {@code true} if the variables are restricted to non-negative values. */ protected boolean restrictToNonNegative() { return nonNegative; } /** * @return the optimization type. */ protected GoalType getGoalType() { return goal; } /** * @return the optimization type. */ protected LinearObjectiveFunction getFunction() { return function; } /** * @return the optimization type. */ protected Collection getConstraints() { return Collections.unmodifiableCollection(linearConstraints); } /** {@inheritDoc} */ public void setMaxIterations(int maxIterations) { this.maxIterations = maxIterations; } /** {@inheritDoc} */ public int getMaxIterations() { return maxIterations; } /** {@inheritDoc} */ public int getIterations() { return iterations; } /** * Increment the iterations counter by 1. * @exception MaxCountExceededException if the maximal number of iterations is exceeded */ protected void incrementIterationsCounter() throws MaxCountExceededException { if (++iterations > maxIterations) { throw new MaxCountExceededException(maxIterations); } } /** {@inheritDoc} */ public PointValuePair optimize(final LinearObjectiveFunction f, final Collection constraints, final GoalType goalType, final boolean restrictToNonNegative) throws MathIllegalStateException { // store linear problem characteristics this.function = f; this.linearConstraints = constraints; this.goal = goalType; this.nonNegative = restrictToNonNegative; iterations = 0; // solve the problem return doOptimize(); } /** * Perform the bulk of optimization algorithm. * @return the point/value pair giving the optimal value for objective function * @exception MathIllegalStateException if no solution fulfilling the constraints * can be found in the allowed number of iterations */ protected abstract PointValuePair doOptimize() throws MathIllegalStateException; }




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