source: branches/2205_OptimizationNetworks/HeuristicLab.Problems.FacilityLocation.CplexSolver/3.3/FLPCplexSolver.cs @ 17456

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2017 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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.IO;
using System.Linq;
using System.Reflection;
using System.Threading;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;
using ILOG.CPLEX;
using ILOG.OPL;

namespace HeuristicLab.Problems.FacilityLocation.CplexSolver {
  public enum FlpVariant { FLP_1, FLP_2 }

  [Item("FLP CPLEX Solver", "Solves facility location problem (FLP) instances using CPLEX.")]
  [Creatable(CreatableAttribute.Categories.SingleSolutionAlgorithms)]
  [StorableClass]
  public sealed class FLPCplexSolver : BasicAlgorithm {
    public override bool SupportsPause {
      get { return false; }
    }

    public override Type ProblemType {
      get { return typeof(FacilityLocationProblem); }
    }

    public new FacilityLocationProblem Problem {
      get { return (FacilityLocationProblem)base.Problem; }
      set { base.Problem = value; }
    }

    [Storable]
    private IFixedValueParameter<TimeSpanValue> maximumRuntimeParameter;
    public IFixedValueParameter<TimeSpanValue> MaximumRuntimeParameter {
      get { return maximumRuntimeParameter; }
    }

    public TimeSpan MaximumRuntime {
      get { return maximumRuntimeParameter.Value.Value; }
      set { maximumRuntimeParameter.Value.Value = value; }
    }

    [Storable]
    private IFixedValueParameter<EnumValue<FlpVariant>> flpVariantParameter;
    public IFixedValueParameter<EnumValue<FlpVariant>> FlpVariantParameter {
      get { return flpVariantParameter; }
    }

    public FlpVariant FlpVariant {
      get { return flpVariantParameter.Value.Value; }
      set { flpVariantParameter.Value.Value = value; }
    }

    [StorableConstructor]
    private FLPCplexSolver(bool deserializing) : base(deserializing) { }
    private FLPCplexSolver(FLPCplexSolver original, Cloner cloner)
      : base(original, cloner) {
      maximumRuntimeParameter = cloner.Clone(original.maximumRuntimeParameter);
      flpVariantParameter = cloner.Clone(original.flpVariantParameter);
    }
    public FLPCplexSolver() {
      Parameters.Add(maximumRuntimeParameter = new FixedValueParameter<TimeSpanValue>("Maximum Runtime", "Specifies how long CPLEX should be allowed to run.", new TimeSpanValue(TimeSpan.FromSeconds(60))));
      Parameters.Add(flpVariantParameter = new FixedValueParameter<EnumValue<FlpVariant>>("FLP Variant", "Which FLP variant should be run.", new EnumValue<FlpVariant>(FlpVariant.FLP_1)));
      Problem = new FacilityLocationProblem();
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new FLPCplexSolver(this, cloner);
    }

    protected override void Run(CancellationToken cancellationToken) {
      var factory = new OplFactory();
      var cplex = factory.CreateCplex();


      var model = Assembly.GetExecutingAssembly().GetManifestResourceNames().SingleOrDefault(x => x.EndsWith(@"." + FlpVariant.ToString() + ".mod"));
      var modelStream = Assembly.GetExecutingAssembly().GetManifestResourceStream(model);

      var depots = Problem.DepotCapacitiesParameter.Value.Length;
      var customers = Problem.CustomerDemandsParameter.Value.Length;

      using (var reader = new StreamReader(modelStream))
      using (var modelSource = factory.CreateOplModelSourceFromString(reader.ReadToEnd(), Path.GetFileNameWithoutExtension(model)))
      using (var errorHandler = factory.CreateOplErrorHandler())
      using (var settings = factory.CreateOplSettings(errorHandler))
      using (var def = factory.CreateOplModelDefinition(modelSource, settings))
      using (var opl = factory.CreateOplModel(def, cplex))
      using (var dataSource = new FLPDataSource(factory, Problem)) {
        opl.AddDataSource(dataSource);
        opl.Generate();
        cplex.SetParam(Cplex.DoubleParam.TiLim, MaximumRuntimeParameter.Value.Value.TotalSeconds);
        var solved = cplex.Solve();
        var assignment = new IntegerVector(customers);
        if (solved) {
          Results.Add(new Result("BestQuality", new DoubleValue(cplex.ObjValue)));
          Results.Add(new Result("Best Solution Optimal", new BoolValue(
            opl.Cplex.GetCplexStatus().Equals(Cplex.CplexStatus.Optimal)
            || opl.Cplex.GetCplexStatus().Equals(Cplex.CplexStatus.OptimalTol))));
          Results.Add(new Result("Best Solution Feasible", new BoolValue(true)));

          var sol = opl.GetElement(FLPDataSource.CustomerDepotAssignment).AsIntMap();

          for (var i = 0; i < depots; i++) {
            var solI = sol.GetSub(i);
            for (var j = 0; j < customers; j++) {
              var solIJ = solI.Get(j);
              if (solIJ == 0) continue;
              assignment[j] = i;
            }
          }
        } else {
          var demands = Problem.CustomerDemandsParameter.Value;
          var capacities = Problem.DepotCapacitiesParameter.Value;

          assignment.Randomize(new FastRandom(), 0, depots); // output a random solution

          Results.Add(new Result("Best Solution Optimal", new BoolValue(false)));
          var feasible = assignment.Select((v, i) => new { Demand = demands[i], Depot = v }).GroupBy(x => x.Depot, x => x.Demand).All(x => capacities[x.Key] <= x.Sum());
          Results.Add(new Result("Best Solution Feasible", new BoolValue(feasible)));
          Results.Add(new Result("BestQuality", new DoubleValue(Problem.Evaluate(assignment))));
        }
        Results.Add(new Result("Best Solution", assignment));
      }
    }
  }
}