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.io.IOException; 020import java.io.ObjectInputStream; 021import java.io.ObjectOutputStream; 022import java.io.Serializable; 023import org.apache.commons.math3.analysis.MultivariateFunction; 024import org.apache.commons.math3.linear.MatrixUtils; 025import org.apache.commons.math3.linear.RealVector; 026import org.apache.commons.math3.linear.ArrayRealVector; 027import org.apache.commons.math3.optim.OptimizationData; 028 029/** 030 * An objective function for a linear optimization problem. 031 * <p> 032 * A linear objective function has one the form: 033 * <pre> 034 * c<sub>1</sub>x<sub>1</sub> + ... c<sub>n</sub>x<sub>n</sub> + d 035 * </pre> 036 * The c<sub>i</sub> and d are the coefficients of the equation, 037 * the x<sub>i</sub> are the coordinates of the current point. 038 * </p> 039 * 040 * @since 2.0 041 */ 042public class LinearObjectiveFunction 043 implements MultivariateFunction, 044 OptimizationData, 045 Serializable { 046 /** Serializable version identifier. */ 047 private static final long serialVersionUID = -4531815507568396090L; 048 /** Coefficients of the linear equation (c<sub>i</sub>). */ 049 private final transient RealVector coefficients; 050 /** Constant term of the linear equation. */ 051 private final double constantTerm; 052 053 /** 054 * @param coefficients Coefficients for the linear equation being optimized. 055 * @param constantTerm Constant term of the linear equation. 056 */ 057 public LinearObjectiveFunction(double[] coefficients, double constantTerm) { 058 this(new ArrayRealVector(coefficients), constantTerm); 059 } 060 061 /** 062 * @param coefficients Coefficients for the linear equation being optimized. 063 * @param constantTerm Constant term of the linear equation. 064 */ 065 public LinearObjectiveFunction(RealVector coefficients, double constantTerm) { 066 this.coefficients = coefficients; 067 this.constantTerm = constantTerm; 068 } 069 070 /** 071 * Gets the coefficients of the linear equation being optimized. 072 * 073 * @return coefficients of the linear equation being optimized. 074 */ 075 public RealVector getCoefficients() { 076 return coefficients; 077 } 078 079 /** 080 * Gets the constant of the linear equation being optimized. 081 * 082 * @return constant of the linear equation being optimized. 083 */ 084 public double getConstantTerm() { 085 return constantTerm; 086 } 087 088 /** 089 * Computes the value of the linear equation at the current point. 090 * 091 * @param point Point at which linear equation must be evaluated. 092 * @return the value of the linear equation at the current point. 093 */ 094 public double value(final double[] point) { 095 return value(new ArrayRealVector(point, false)); 096 } 097 098 /** 099 * Computes the value of the linear equation at the current point. 100 * 101 * @param point Point at which linear equation must be evaluated. 102 * @return the value of the linear equation at the current point. 103 */ 104 public double value(final RealVector point) { 105 return coefficients.dotProduct(point) + constantTerm; 106 } 107 108 /** {@inheritDoc} */ 109 @Override 110 public boolean equals(Object other) { 111 if (this == other) { 112 return true; 113 } 114 if (other instanceof LinearObjectiveFunction) { 115 LinearObjectiveFunction rhs = (LinearObjectiveFunction) other; 116 return (constantTerm == rhs.constantTerm) && coefficients.equals(rhs.coefficients); 117 } 118 119 return false; 120 } 121 122 /** {@inheritDoc} */ 123 @Override 124 public int hashCode() { 125 return Double.valueOf(constantTerm).hashCode() ^ coefficients.hashCode(); 126 } 127 128 /** 129 * Serialize the instance. 130 * @param oos stream where object should be written 131 * @throws IOException if object cannot be written to stream 132 */ 133 private void writeObject(ObjectOutputStream oos) 134 throws IOException { 135 oos.defaultWriteObject(); 136 MatrixUtils.serializeRealVector(coefficients, oos); 137 } 138 139 /** 140 * Deserialize the instance. 141 * @param ois stream from which the object should be read 142 * @throws ClassNotFoundException if a class in the stream cannot be found 143 * @throws IOException if object cannot be read from the stream 144 */ 145 private void readObject(ObjectInputStream ois) 146 throws ClassNotFoundException, IOException { 147 ois.defaultReadObject(); 148 MatrixUtils.deserializeRealVector(this, "coefficients", ois); 149 } 150}