source: branches/1614_GeneralizedQAP/HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms/3.3/LocalSolverNet/GQAPBinarySolver.cs @ 15700

Last change on this file since 15700 was 15700, checked in by abeham, 2 years ago

#1614:

  • Changed performance measure to stopwatch instead of datetime for precision reasons
File size: 8.2 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Threading;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.IntegerVectorEncoding;
28using HeuristicLab.Optimization;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using localsolver;
31
32namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.LocalSolverNet {
33  [Item("LocalSolver Binary (GQAP)", "LocalSolver algorithm solving the GQAP using 0-1 decision variables")]
34  [StorableClass]
35  [Creatable(CreatableAttribute.Categories.Algorithms)]
36  public sealed class GQAPBinarySolver : ContextAlgorithm<LocalSolverContext, IntegerVectorEncoding> {
37    public override bool SupportsPause {
38      get { return false; }
39    }
40
41    public override Type ProblemType {
42      get { return typeof(GQAP); }
43    }
44
45    public new GQAP Problem {
46      get { return (GQAP)base.Problem; }
47      set { base.Problem = value; }
48    }
49
50    // LS Program variables
51    private LSExpression[][] x;
52    private LSExpression[] equipmentsOnLocations;
53    private LSExpression obj;
54    private LocalSolver localSolver;
55
56
57    [StorableConstructor]
58    private GQAPBinarySolver(bool deserializing) : base(deserializing) { }
59    private GQAPBinarySolver(GQAPBinarySolver original, Cloner cloner)
60    : base(original, cloner) {
61    }
62    public GQAPBinarySolver() {
63      Problem = new GQAP();
64      MaximumEvaluationsParameter.Hidden = true;
65      MaximumIterationsParameter.Hidden = true;
66    }
67
68    public override IDeepCloneable Clone(Cloner cloner) {
69      return new GQAPBinarySolver(this, cloner);
70    }
71
72    private double prevObj;
73    private DateTime lastUpdate;
74    private CancellationToken token;
75
76    private void LocalSolverOnIterationTicked(LocalSolver ls, LSCallbackType type) {
77      IResult result;
78      Context.Iterations++;
79      if ((DateTime.UtcNow - lastUpdate) > TimeSpan.FromSeconds(1)) {
80        if (Results.TryGetValue("Iterations", out result))
81          ((IntValue)result.Value).Value = Context.Iterations;
82        else Results.Add(new Result("Iterations", new IntValue(Context.Iterations)));
83        lastUpdate = DateTime.UtcNow;
84      }
85
86      if (token.IsCancellationRequested) localSolver.Stop();
87
88      var curObj = obj.GetDoubleValue();
89
90      if (curObj >= prevObj) return;
91      prevObj = curObj;
92      Context.BestQuality = curObj;
93           
94      if (Results.TryGetValue("BestQuality", out result))
95        ((DoubleValue)result.Value).Value = Context.BestQuality;
96      else Results.Add(new Result("BestQuality", new DoubleValue(Context.BestQuality)));
97
98      var locations = Problem.ProblemInstance.Capacities.Length;
99      var best = new int[Problem.ProblemInstance.Demands.Length];
100      for (var i = 0; i < best.Length; i++) {
101        for (var j = 0; j < locations; j++) {
102          if (x[i][j].GetIntValue() == 1) {
103            best[i] = j;
104            break;
105          }
106        }
107      }
108      var bestVec = new IntegerVector(best);
109      var eval = Problem.ProblemInstance.Evaluate(bestVec);
110      Context.BestSolution = new GQAPSolution(bestVec, eval);
111
112      var scope = Context.ToScope(new GQAPSolution(new IntegerVector(best), (Evaluation)eval.Clone()), Problem.ProblemInstance.ToSingleObjective(eval));
113      Context.ReplaceIncumbent(scope);
114
115      if (Results.TryGetValue("BestSolution", out result))
116        result.Value = Context.BestSolution;
117      else Results.Add(new Result("BestSolution", Context.BestSolution));
118
119      Context.RunOperator(Analyzer, CancellationToken.None);
120
121      if (StoppingCriterion()) localSolver.Stop();
122    }
123
124    protected override void Initialize(CancellationToken cancellationToken) {
125      base.Initialize(cancellationToken);
126
127      prevObj = double.MaxValue;
128    }
129
130    protected override void Run(CancellationToken cancellationToken) {
131      base.Run(cancellationToken);
132      token = cancellationToken;
133      lastUpdate = DateTime.UtcNow.AddSeconds(-1);
134      localSolver = new LocalSolver();
135
136      // Declares the optimization model
137      LSModel model = localSolver.GetModel();
138
139      var data = Problem.ProblemInstance;
140
141      // x[f,l] = 1 if equipments f is on location l, 0 otherwise
142      x = new LSExpression[data.Demands.Length][];
143      for (int f = 0; f < data.Demands.Length; f++) {
144        x[f] = new LSExpression[data.Capacities.Length];
145        for (int l = 0; l < data.Capacities.Length; l++) {
146          x[f][l] = model.Bool();
147        }
148      }
149
150      // All equipments are installed in exactly 1 location
151      for (int f = 0; f < data.Demands.Length; f++) {
152        LSExpression nbLocationsAssigned = model.Sum();
153        for (int l = 0; l < data.Capacities.Length; l++) {
154          nbLocationsAssigned.AddOperand(x[f][l]);
155        }
156        model.Constraint(nbLocationsAssigned == 1);
157      }
158
159      // All locations contain not more equipments than there is capacity for
160      for (int l = 0; l < data.Capacities.Length; l++) {
161        LSExpression assignedDemand = model.Sum();
162        for (int f = 0; f < data.Demands.Length; f++) {
163          assignedDemand.AddOperand(x[f][l] * data.Demands[f]);
164        }
165        model.Constraint(assignedDemand <= data.Capacities[l]);
166      }
167
168      // Index of the assigned location of equipment f
169      equipmentsOnLocations = new LSExpression[data.Demands.Length];
170      for (int f = 0; f < data.Demands.Length; f++) {
171        equipmentsOnLocations[f] = model.Sum();
172        for (int l = 0; l < data.Capacities.Length; l++) {
173          equipmentsOnLocations[f].AddOperand(l * x[f][l]);
174        }
175      }
176
177      // Create distances as an array to be accessed by an at operator
178      var distancesJagged = new double[data.Capacities.Length][];
179      for (var i = 0; i < data.Capacities.Length; i++) {
180        distancesJagged[i] = new double[data.Capacities.Length];
181        for (var j = 0; j < data.Capacities.Length; j++)
182          distancesJagged[i][j] = data.Distances[i, j];
183      }
184      var installJagged = new double[data.Demands.Length][];
185      for (var i = 0; i < data.Demands.Length; i++) {
186        installJagged[i] = new double[data.Capacities.Length];
187        for (var j = 0; j < data.Capacities.Length; j++)
188          installJagged[i][j] = data.InstallationCosts[i, j];
189      }
190      LSExpression distancesArray = model.Array(distancesJagged);
191      LSExpression installCostsArray = model.Array(installJagged);
192
193      // Minimize the sum of product distance*flow
194      obj = model.Sum();
195      for (int f1 = 0; f1 < data.Demands.Length; f1++) {
196        for (int f2 = 0; f2 < data.Demands.Length; f2++) {
197          obj.AddOperand(data.TransportationCosts * data.Weights[f1, f2] * distancesArray[equipmentsOnLocations[f1], equipmentsOnLocations[f2]]);
198        }
199        obj.AddOperand(installCostsArray[f1, equipmentsOnLocations[f1]]);
200      }
201
202      model.Minimize(obj);
203
204      try {
205        model.Close();
206
207        // Parameterizes the solver.
208        LSPhase phase = localSolver.CreatePhase();
209        phase.SetTimeLimit((int)Math.Ceiling(MaximumRuntime.TotalSeconds));
210
211        localSolver.AddCallback(LSCallbackType.IterationTicked, LocalSolverOnIterationTicked);
212
213        localSolver.Solve();
214
215        localSolver.RemoveCallback(LSCallbackType.IterationTicked, LocalSolverOnIterationTicked);
216      } finally {
217        localSolver.Dispose();
218      }
219
220      Context.RunOperator(Analyzer, CancellationToken.None);
221    }
222  }
223}
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