Java tutorial
/** * Copyright (C) 2013-2017 Vasilis Vryniotis <bbriniotis@datumbox.com> * * Licensed 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 com.datumbox.framework.core.mathematics.linearprogramming; import com.datumbox.framework.core.common.utilities.PHPMethods; import org.apache.commons.math3.optim.PointValuePair; import org.apache.commons.math3.optim.linear.*; import org.apache.commons.math3.optim.nonlinear.scalar.GoalType; import java.util.ArrayList; import java.util.List; /** * The LPSolver provides an easy way to formulate and solve Linear Programming * problems. * * @author Vasilis Vryniotis <bbriniotis@datumbox.com> */ public class LPSolver { /** * Greater or equal. */ public static String GEQ = ">="; /** * Less or equal */ public static String LEQ = "<="; /** * Equal. */ public static String EQ = "="; /** * The Result class of the LP problem. */ public static class LPResult { private Double objectiveValue; private double[] variableValues; /** * Getter for the Objective value. * * @return */ public Double getObjectiveValue() { return objectiveValue; } /** * Setter for the Objective value. * * @param objectiveValue */ protected void setObjectiveValue(Double objectiveValue) { this.objectiveValue = objectiveValue; } /** * Getter for the values of the Variables. * * @return */ public double[] getVariableValues() { return PHPMethods.array_clone(variableValues); } /** * Setter for the values of the Variables. * * @param variableValues */ protected void setVariableValues(double[] variableValues) { this.variableValues = PHPMethods.array_clone(variableValues); } } /** * The LP Constraint is an internal class which stores the the main body of * the constraint, the sign and the right value. */ public static class LPConstraint { /** * The body of the constraint; the left part of the constraint. */ private final double[] contraintBody; /** * The sign symbol: ">=", "<=", "=". */ private final String sign; /** * The value of the constraint; the right part of the constraint. */ private final double value; /** * The constructor of LP Constraint. * * @param constraintBody The array with the parameters of the constrain * @param sign The sign of the constrain * @param value The right part value of the constrain */ public LPConstraint(double[] constraintBody, String sign, double value) { this.contraintBody = PHPMethods.array_clone(constraintBody); this.sign = sign; this.value = value; } /** * Getter for the body of the constraint. * * @return */ public double[] getContraintBody() { return PHPMethods.array_clone(contraintBody); } /** * Getter for the sign of the constraint. * * @return */ public String getSign() { return sign; } /** * Getter for the value of the constraint. * * @return */ public double getValue() { return value; } } /** * Solves the LP problem and returns the result. * * @param linearObjectiveFunction * @param linearConstraintsList * @param nonNegative * @param maximize * @return */ public static LPResult solve(double[] linearObjectiveFunction, List<LPSolver.LPConstraint> linearConstraintsList, boolean nonNegative, boolean maximize) { int m = linearConstraintsList.size(); List<LinearConstraint> constraints = new ArrayList<>(m); for (LPSolver.LPConstraint constraint : linearConstraintsList) { String sign = constraint.getSign(); Relationship relationship = null; if (LPSolver.GEQ.equals(sign)) { relationship = Relationship.GEQ; } else if (LPSolver.LEQ.equals(sign)) { relationship = Relationship.LEQ; } else if (LPSolver.EQ.equals(sign)) { relationship = Relationship.EQ; } constraints .add(new LinearConstraint(constraint.getContraintBody(), relationship, constraint.getValue())); } SimplexSolver solver = new SimplexSolver(); PointValuePair solution = solver.optimize(new LinearObjectiveFunction(linearObjectiveFunction, 0.0), new LinearConstraintSet(constraints), maximize ? GoalType.MAXIMIZE : GoalType.MINIMIZE, new NonNegativeConstraint(nonNegative), PivotSelectionRule.BLAND); LPResult result = new LPResult(); result.setObjectiveValue(solution.getValue()); result.setVariableValues(solution.getPoint()); return result; } }