#region License Information /* HeuristicLab * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Threading; using Google.OrTools.LinearSolver; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.ExactOptimization.LinearProgramming { [Item("Mixed-Integer Linear Programming (LP, MIP)", "Linear/mixed integer programming implemented in several solvers. " + "See also https://dev.heuristiclab.com/trac.fcgi/wiki/Documentation/Reference/ExactOptimization")] [Creatable(CreatableAttribute.Categories.ExactAlgorithms)] [StorableClass] public sealed class LinearProgrammingAlgorithm : BasicAlgorithm { [Storable] private readonly IFixedValueParameter dualToleranceParam; [Storable] private readonly IFixedValueParameter presolveParam; [Storable] private readonly IFixedValueParameter primalToleranceParam; [Storable] private readonly IFixedValueParameter relativeGapToleranceParam; [Storable] private readonly IFixedValueParameter scalingParam; [Storable] private readonly IFixedValueParameter timeLimitParam; [Storable] private IConstrainedValueParameter linearSolverParam; #region Problem Properties public new LinearProblem Problem { get => (LinearProblem)base.Problem; set => base.Problem = value; } public override Type ProblemType { get; } = typeof(LinearProblem); #endregion #region Parameter Properties public IFixedValueParameter DualToleranceParameter => dualToleranceParam; public IConstrainedValueParameter LinearSolverParameter => linearSolverParam; public IFixedValueParameter PresolveParameter => presolveParam; public IFixedValueParameter PrimalToleranceParameter => primalToleranceParam; public IFixedValueParameter RelativeGapToleranceParameter => relativeGapToleranceParam; public IFixedValueParameter ScalingParameter => scalingParam; public IFixedValueParameter TimeLimitParameter => timeLimitParam; #endregion #region Properties public double DualTolerance { get => dualToleranceParam.Value.Value; set => dualToleranceParam.Value.Value = value; } public ILinearSolver LinearSolver { get => linearSolverParam.Value; set => linearSolverParam.Value = value; } public bool Presolve { get => presolveParam.Value.Value; set => presolveParam.Value.Value = value; } public double PrimalTolerance { get => primalToleranceParam.Value.Value; set => primalToleranceParam.Value.Value = value; } public double RelativeGapTolerance { get => relativeGapToleranceParam.Value.Value; set => relativeGapToleranceParam.Value.Value = value; } public bool Scaling { get => scalingParam.Value.Value; set => scalingParam.Value.Value = value; } public override bool SupportsPause => LinearSolver.SupportsPause; public override bool SupportsStop => LinearSolver.SupportsStop; public TimeSpan TimeLimit { get => timeLimitParam.Value.Value; set => timeLimitParam.Value.Value = value; } #endregion public LinearProgrammingAlgorithm() { Parameters.Add(linearSolverParam = new ConstrainedValueParameter(nameof(LinearSolver), "The solver used to solve the model.")); ILinearSolver defaultSolver; linearSolverParam.ValidValues.Add(defaultSolver = new CoinOrSolver()); linearSolverParam.ValidValues.Add(new CplexSolver()); linearSolverParam.ValidValues.Add(new GlopSolver()); linearSolverParam.ValidValues.Add(new GurobiSolver()); linearSolverParam.ValidValues.Add(new ScipSolver()); linearSolverParam.Value = defaultSolver; Parameters.Add(relativeGapToleranceParam = new FixedValueParameter(nameof(RelativeGapTolerance), "Limit for relative MIP gap.", new PercentValue(SolverParameters.DefaultRelativeMipGap))); Parameters.Add(timeLimitParam = new FixedValueParameter(nameof(TimeLimit), "Limit for runtime. Set to zero for unlimited runtime.", new TimeSpanValue(new TimeSpan(0, 1, 0)))); Parameters.Add(presolveParam = new FixedValueParameter(nameof(Presolve), "Advanced usage: presolve mode.", new BoolValue(SolverParameters.DefaultPresolve == SolverParameters.PresolveValues.PresolveOn)) { Hidden = true }); Parameters.Add(dualToleranceParam = new FixedValueParameter(nameof(DualTolerance), "Advanced usage: tolerance for dual feasibility of basic solutions.", new DoubleValue(SolverParameters.DefaultDualTolerance)) { Hidden = true }); Parameters.Add(primalToleranceParam = new FixedValueParameter(nameof(PrimalTolerance), "Advanced usage: tolerance for primal feasibility of basic solutions. " + "This does not control the integer feasibility tolerance of integer " + "solutions for MIP or the tolerance used during presolve.", new DoubleValue(SolverParameters.DefaultPrimalTolerance)) { Hidden = true }); Parameters.Add(scalingParam = new FixedValueParameter(nameof(Scaling), "Advanced usage: enable or disable matrix scaling.", new BoolValue()) { Hidden = true }); Problem = new LinearProblem(); } [StorableConstructor] private LinearProgrammingAlgorithm(bool deserializing) : base(deserializing) { } private LinearProgrammingAlgorithm(LinearProgrammingAlgorithm original, Cloner cloner) : base(original, cloner) { linearSolverParam = cloner.Clone(original.linearSolverParam); relativeGapToleranceParam = cloner.Clone(original.relativeGapToleranceParam); timeLimitParam = cloner.Clone(original.timeLimitParam); presolveParam = cloner.Clone(original.presolveParam); dualToleranceParam = cloner.Clone(original.dualToleranceParam); primalToleranceParam = cloner.Clone(original.primalToleranceParam); scalingParam = cloner.Clone(original.scalingParam); } public override IDeepCloneable Clone(Cloner cloner) => new LinearProgrammingAlgorithm(this, cloner); public override void Pause() { base.Pause(); LinearSolver.InterruptSolve(); } public override void Prepare() { base.Prepare(); Results.Clear(); foreach (var solver in linearSolverParam.ValidValues) { solver.Reset(); } } public override void Stop() { base.Stop(); LinearSolver.InterruptSolve(); } protected override void Run(CancellationToken cancellationToken) { LinearSolver.PrimalTolerance = PrimalTolerance; LinearSolver.DualTolerance = DualTolerance; LinearSolver.Presolve = Presolve; LinearSolver.RelativeGapTolerance = RelativeGapTolerance; LinearSolver.Scaling = Scaling; LinearSolver.TimeLimit = TimeLimit; LinearSolver.Solve(Problem.ProblemDefinition, Results, cancellationToken); } } }