All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.ojalgo.commons.math3.optim.linear.SolverCommonsMath Maven / Gradle / Ivy

There is a newer version: 4.0.0
Show newest version
/*
 * Copyright 1997-2022 Optimatika
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
package org.ojalgo.commons.math3.optim.linear;

import static org.ojalgo.function.constant.PrimitiveMath.*;

import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Optional;
import java.util.Set;

import org.apache.commons.math3.optim.OptimizationData;
import org.apache.commons.math3.optim.PointValuePair;
import org.apache.commons.math3.optim.linear.LinearConstraint;
import org.apache.commons.math3.optim.linear.LinearConstraintSet;
import org.apache.commons.math3.optim.linear.LinearObjectiveFunction;
import org.apache.commons.math3.optim.linear.NoFeasibleSolutionException;
import org.apache.commons.math3.optim.linear.NonNegativeConstraint;
import org.apache.commons.math3.optim.linear.Relationship;
import org.apache.commons.math3.optim.linear.SimplexSolver;
import org.apache.commons.math3.optim.linear.UnboundedSolutionException;
import org.apache.commons.math3.optim.nonlinear.scalar.GoalType;
import org.ojalgo.optimisation.ExpressionsBasedModel;
import org.ojalgo.optimisation.Optimisation;
import org.ojalgo.optimisation.Variable;
import org.ojalgo.structure.Access1D;
import org.ojalgo.structure.Structure1D.IntIndex;

/**
 * Use Apache's {@link SimplexSolver} from ojAlgo's {@link ExpressionsBasedModel}.
 * 

* Just call {@link ExpressionsBasedModel#addIntegration(ExpressionsBasedModel.Integration)} with * {@link SolverCommonsMath#INTEGRATION} as the argument. * * @author apete */ public final class SolverCommonsMath implements Optimisation.Solver { @FunctionalInterface public interface Configurator { void configure(SimplexSolver solver, Optimisation.Options options); } public static final class Integration extends ExpressionsBasedModel.Integration { Integration() { super(); } public SolverCommonsMath build(final ExpressionsBasedModel model) { Set optimizationData = new HashSet<>(); List variables = model.getVariables(); int nbVariables = variables.size(); double[] weights = model.objective().toFunction().getLinearFactors().toRawCopy1D(); if (weights.length != nbVariables) { throw new IllegalStateException(); } optimizationData.add(new LinearObjectiveFunction(weights, ZERO)); optimizationData.add(model.getOptimisationSense() == Optimisation.Sense.MAX ? GoalType.MAXIMIZE : GoalType.MINIMIZE); List constraints = new ArrayList<>(); model.constraints().forEach(expr -> { double[] coeffs = new double[nbVariables]; Set keySet = expr.getLinearKeySet(); for (IntIndex tmpIntIndex : keySet) { coeffs[tmpIntIndex.index] = expr.getAdjustedLinearFactor(tmpIntIndex); } if (expr.isEqualityConstraint()) { constraints.add(new LinearConstraint(coeffs, Relationship.EQ, expr.getAdjustedUpperLimit())); } else { if (expr.isLowerConstraint()) { constraints.add(new LinearConstraint(coeffs, Relationship.GEQ, expr.getAdjustedLowerLimit())); } if (expr.isUpperConstraint()) { constraints.add(new LinearConstraint(coeffs, Relationship.LEQ, expr.getAdjustedUpperLimit())); } } }); boolean anyVariableNegative = false; Variable tmpVariable; for (int i = 0; i < nbVariables; i++) { tmpVariable = variables.get(i); anyVariableNegative |= tmpVariable.isNegative(); if (tmpVariable.isConstraint()) { double[] coeffs = new double[nbVariables]; coeffs[i] = tmpVariable.getAdjustmentFactor(); if (tmpVariable.isEqualityConstraint()) { constraints.add(new LinearConstraint(coeffs, Relationship.EQ, tmpVariable.getAdjustedUpperLimit())); } else { if (tmpVariable.isLowerConstraint()) { constraints.add(new LinearConstraint(coeffs, Relationship.GEQ, tmpVariable.getAdjustedLowerLimit())); } if (tmpVariable.isUpperConstraint()) { constraints.add(new LinearConstraint(coeffs, Relationship.LEQ, tmpVariable.getAdjustedUpperLimit())); } } } } optimizationData.add(new LinearConstraintSet(constraints)); optimizationData.add(new NonNegativeConstraint(!anyVariableNegative)); return new SolverCommonsMath(optimizationData, model.options); } public boolean isCapable(final ExpressionsBasedModel model) { return !model.isAnyVariableInteger() && !model.isAnyExpressionQuadratic(); } @Override protected boolean isSolutionMapped() { return false; } } public static final SolverCommonsMath.Integration INTEGRATION = new Integration(); static final Configurator DEFAULT = (solver, options) -> { // TODO Auto-generated method stub }; private final Set myModelData; private final Optimisation.Options myOptions; SolverCommonsMath(final Set modelData, final Optimisation.Options options) { super(); myModelData = modelData; myOptions = options; } public Optimisation.Result solve(final Result kickStarter) { // InitialGuess guess = new InitialGuess(kickStarter.toRawCopy1D()); // // myModelData.add(guess); Optimisation.State state = Optimisation.State.FAILED; double value = Double.NaN; Access1D solution = kickStarter; try { SimplexSolver solver = new SimplexSolver(); DEFAULT.configure(solver, myOptions); Optional optional = myOptions.getConfigurator(Configurator.class); if (optional.isPresent()) { optional.get().configure(solver, myOptions); } PointValuePair solutionAndValue = solver.optimize(myModelData.toArray(new OptimizationData[myModelData.size()])); state = Optimisation.State.OPTIMAL; value = solutionAndValue.getValue().doubleValue(); solution = Access1D.wrap(solutionAndValue.getPoint()); } catch (NoFeasibleSolutionException infeasible) { state = Optimisation.State.INFEASIBLE; } catch (UnboundedSolutionException unbounded) { state = Optimisation.State.UNBOUNDED; } return new Optimisation.Result(state, value, solution); } }





© 2015 - 2024 Weber Informatics LLC | Privacy Policy