001/* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017package org.apache.commons.math3.optim.linear; 018 019import java.util.Collection; 020import java.util.Collections; 021import org.apache.commons.math3.exception.TooManyIterationsException; 022import org.apache.commons.math3.optim.OptimizationData; 023import org.apache.commons.math3.optim.PointValuePair; 024import org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer; 025 026/** 027 * Base class for implementing linear optimizers. 028 * 029 * @since 3.1 030 */ 031public abstract class LinearOptimizer 032 extends MultivariateOptimizer { 033 /** 034 * Linear objective function. 035 */ 036 private LinearObjectiveFunction function; 037 /** 038 * Linear constraints. 039 */ 040 private Collection<LinearConstraint> linearConstraints; 041 /** 042 * Whether to restrict the variables to non-negative values. 043 */ 044 private boolean nonNegative; 045 046 /** 047 * Simple constructor with default settings. 048 * 049 */ 050 protected LinearOptimizer() { 051 super(null); // No convergence checker. 052 } 053 054 /** 055 * @return {@code true} if the variables are restricted to non-negative values. 056 */ 057 protected boolean isRestrictedToNonNegative() { 058 return nonNegative; 059 } 060 061 /** 062 * @return the optimization type. 063 */ 064 protected LinearObjectiveFunction getFunction() { 065 return function; 066 } 067 068 /** 069 * @return the optimization type. 070 */ 071 protected Collection<LinearConstraint> getConstraints() { 072 return Collections.unmodifiableCollection(linearConstraints); 073 } 074 075 /** 076 * {@inheritDoc} 077 * 078 * @param optData Optimization data. In addition to those documented in 079 * {@link MultivariateOptimizer#parseOptimizationData(OptimizationData[]) 080 * MultivariateOptimizer}, this method will register the following data: 081 * <ul> 082 * <li>{@link LinearObjectiveFunction}</li> 083 * <li>{@link LinearConstraintSet}</li> 084 * <li>{@link NonNegativeConstraint}</li> 085 * </ul> 086 * @return {@inheritDoc} 087 * @throws TooManyIterationsException if the maximal number of 088 * iterations is exceeded. 089 */ 090 @Override 091 public PointValuePair optimize(OptimizationData... optData) 092 throws TooManyIterationsException { 093 // Set up base class and perform computation. 094 return super.optimize(optData); 095 } 096 097 /** 098 * Scans the list of (required and optional) optimization data that 099 * characterize the problem. 100 * 101 * @param optData Optimization data. 102 * The following data will be looked for: 103 * <ul> 104 * <li>{@link LinearObjectiveFunction}</li> 105 * <li>{@link LinearConstraintSet}</li> 106 * <li>{@link NonNegativeConstraint}</li> 107 * </ul> 108 */ 109 @Override 110 protected void parseOptimizationData(OptimizationData... optData) { 111 // Allow base class to register its own data. 112 super.parseOptimizationData(optData); 113 114 // The existing values (as set by the previous call) are reused if 115 // not provided in the argument list. 116 for (OptimizationData data : optData) { 117 if (data instanceof LinearObjectiveFunction) { 118 function = (LinearObjectiveFunction) data; 119 continue; 120 } 121 if (data instanceof LinearConstraintSet) { 122 linearConstraints = ((LinearConstraintSet) data).getConstraints(); 123 continue; 124 } 125 if (data instanceof NonNegativeConstraint) { 126 nonNegative = ((NonNegativeConstraint) data).isRestrictedToNonNegative(); 127 continue; 128 } 129 } 130 } 131}