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source: branches/OptimizationNetworks/HeuristicLab.Networks.IntegratedOptimization.TravelingThief/3.3/TtpOrchestratorNode3.cs @ 14613

Last change on this file since 14613 was 14610, checked in by jkarder, 8 years ago

#2205: worked on optimization networks

  • added abstract base classes for ttp networks/orchestrators
  • removed ttp networks/orchestrators from HeuristicLab.Networks.IntegratedOptimization
  • runs can now be cleared when preparing OrchestratedAlgorithmNodes
File size: 5.9 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.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Core.Networks;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.BinaryVectorEncoding;
29using HeuristicLab.Encodings.PermutationEncoding;
30using HeuristicLab.Encodings.RealVectorEncoding;
31using HeuristicLab.Optimization;
32using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
33using HeuristicLab.Problems.Knapsack;
34using HeuristicLab.Problems.TravelingSalesman;
35
36namespace HeuristicLab.Networks.IntegratedOptimization.TravelingThief {
37  [Item("TtpOrchestratorNode3", "Orchestrator for TTP optimization network version 3.")]
38  [StorableClass]
39  public sealed class TtpOrchestratorNode3 : TtpOrchestratorNode {
40    [StorableConstructor]
41    private TtpOrchestratorNode3(bool deserializing) : base(deserializing) { }
42    private TtpOrchestratorNode3(TtpOrchestratorNode3 original, Cloner cloner) : base(original, cloner) { }
43    public TtpOrchestratorNode3() : this("TtpOrchestratorNode3") { }
44    public TtpOrchestratorNode3(string name) : base(name) { }
45
46    public override IDeepCloneable Clone(Cloner cloner) {
47      return new TtpOrchestratorNode3(this, cloner);
48    }
49
50    #region MetaSolver Message Handling
51    protected override void MetaSolverEvaluationPortMessage(IMessage message) {
52      var factors = (RealVector)message["RealVector"];
53      int fi = 0;
54
55      var ksp = (BinaryKnapsackProblem)KspParameter.Value.Clone();
56      while (fi < ksp.Values.Length) {
57        ksp.Values[fi] = (int)Math.Ceiling(ksp.Values[fi] * factors[fi]);
58        ++fi;
59      }
60
61      var kspMsg = KspSolverOrchestrationPort.PrepareMessage();
62      kspMsg["OrchestrationMessage"] = new EnumValue<OrchestrationMessage>(OrchestrationMessage.Prepare | OrchestrationMessage.ClearRuns | OrchestrationMessage.Start);
63      kspMsg["Problem"] = ksp;
64      KspSolverOrchestrationPort.SendMessage(kspMsg);
65      cts.Token.ThrowIfCancellationRequested();
66
67      var bestKspSolution = (BinaryVector)kspResults["Best Solution"].Value.Clone();
68      var kspCapacity = (IntValue)KspParameter.Value.KnapsackCapacity.Clone();
69      var kspPenalty = new DoubleValue(0.0);
70      var kspWeights = (IntArray)KspParameter.Value.Weights.Clone();
71      var kspValues = (IntArray)KspParameter.Value.Values.Clone();
72      var bestKspQuality = KnapsackEvaluator.Apply(bestKspSolution, kspCapacity, kspPenalty, kspWeights, kspValues).Quality;
73      var loot = new KnapsackSolution(bestKspSolution, bestKspQuality, kspCapacity, kspWeights, kspValues);
74
75      var tsp = (TravelingSalesmanProblem)TspParameter.Value.Clone();
76      for (int j = 0; j < tsp.Coordinates.Rows; j++) {
77        tsp.Coordinates[j, 0] = (int)Math.Ceiling(tsp.Coordinates[j, 0] * factors[fi + j * 2]);
78        tsp.Coordinates[j, 1] = (int)Math.Ceiling(tsp.Coordinates[j, 1] * factors[fi + j * 2 + 1]);
79      }
80
81      var tspMsg = TspSolverOrchestrationPort.PrepareMessage();
82      tspMsg["OrchestrationMessage"] = new EnumValue<OrchestrationMessage>(OrchestrationMessage.Prepare | OrchestrationMessage.ClearRuns | OrchestrationMessage.Start);
83      var tpp = new TourProfitProblem {
84        Tsp = (TravelingSalesmanProblem)TspParameter.Value.Clone(),
85        Ksp = (BinaryKnapsackProblem)KspParameter.Value.Clone(),
86        FixedKspSolution = bestKspSolution,
87        Availability = AvailabilityParameter.Value.ToArray(),
88        RentingRatio = RentingRatioParameter.Value.Value,
89        MinSpeed = MinSpeedParameter.Value.Value,
90        MaxSpeed = MaxSpeedParameter.Value.Value,
91        DistanceType = distanceType
92      };
93      tpp.Encoding.Length = TspParameter.Value.Coordinates.Rows;
94      tspMsg["Problem"] = tpp;
95      TspSolverOrchestrationPort.SendMessage(tspMsg);
96      cts.Token.ThrowIfCancellationRequested();
97
98      var bestTspSolution = (Permutation)tspResults["Best TSP Solution"].Value.Clone();
99      var coordinates = (DoubleMatrix)TspParameter.Value.Coordinates.Clone();
100      var tour = new PathTSPTour(coordinates, bestTspSolution, new DoubleValue(TSPCoordinatesPathEvaluator.Apply(new TSPEuclideanPathEvaluator(), coordinates, bestTspSolution)));
101
102      #region Analyze
103      double objectiveValue = TtpUtils.Evaluate(TspParameter.Value, tour.Permutation.ToArray(), KspParameter.Value, loot.BinaryVector.ToArray(),
104        AvailabilityParameter.Value.ToArray(), RentingRatioParameter.Value.Value, MinSpeedParameter.Value.Value, MaxSpeedParameter.Value.Value, distanceType);
105      ((DoubleValue)message["Quality"]).Value = objectiveValue;
106
107      IResult bestQuality;
108      if (!Results.TryGetValue("Best TTP Quality", out bestQuality)) {
109        Results.Add(new Result("Best TTP Quality", new DoubleValue(objectiveValue)));
110        Results.Add(new Result("Best Tour", tour));
111        Results.Add(new Result("Best Loot", loot));
112      } else if (objectiveValue > ((DoubleValue)bestQuality.Value).Value) {
113        ((DoubleValue)bestQuality.Value).Value = objectiveValue;
114        Results["Best Tour"].Value = tour;
115        Results["Best Loot"].Value = loot;
116      }
117      #endregion
118    }
119    #endregion
120  }
121}
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