[14601] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Core.Networks;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Encodings.BinaryVectorEncoding;
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| 29 | using HeuristicLab.Encodings.RealVectorEncoding;
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| 30 | using HeuristicLab.Optimization;
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| 31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 32 | using HeuristicLab.Problems.Knapsack;
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| 33 | using HeuristicLab.Problems.TravelingSalesman;
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| 34 |
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| 35 | namespace HeuristicLab.Networks.IntegratedOptimization.TravelingThief {
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| 36 | [Item("TtpOrchestratorNode2", "Orchestrator for TTP optimization network version 2.")]
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| 37 | [StorableClass]
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[14610] | 38 | public sealed class TtpOrchestratorNode2 : TtpOrchestratorNode {
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[14601] | 39 | [StorableConstructor]
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| 40 | private TtpOrchestratorNode2(bool deserializing) : base(deserializing) { }
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[14610] | 41 | private TtpOrchestratorNode2(TtpOrchestratorNode2 original, Cloner cloner) : base(original, cloner) { }
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[14601] | 42 | public TtpOrchestratorNode2() : this("TtpOrchestratorNode2") { }
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[14616] | 43 | public TtpOrchestratorNode2(string name) : base(name) {
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[14628] | 44 | MetaSolverOrchestrationPort = CreateOrchestrationPort<MaximizationVariegationProblem<RealVectorEncoding>>(MetaSolverName + OrchestrationPortNameSuffix);
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| 45 | MetaSolverEvaluationPort = CreateEvaluationPort<RealVector>(MetaSolverName + EvaluationPortNameSuffix, "RealVector", "Quality");
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| 46 | TspSolverOrchestrationPort = CreateOrchestrationPort<TravelingSalesmanProblem>(TspSolverName + OrchestrationPortNameSuffix);
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| 47 | KspSolverOrchestrationPort = CreateOrchestrationPort<LootProfitProblem>(KspSolverName + OrchestrationPortNameSuffix);
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[14616] | 48 | }
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[14601] | 49 |
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| 50 | public override IDeepCloneable Clone(Cloner cloner) {
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| 51 | return new TtpOrchestratorNode2(this, cloner);
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| 52 | }
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| 53 |
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[14616] | 54 | public override void Prepare(bool clearRuns = false) {
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| 55 | base.Prepare(clearRuns);
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| 56 |
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| 57 | var metaMsg = MetaSolverOrchestrationPort.PrepareMessage();
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| 58 | var msgFlags = OrchestrationMessage.Prepare | OrchestrationMessage.SetEvalHook;
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| 59 | if (clearRuns) msgFlags |= OrchestrationMessage.ClearRuns;
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| 60 | metaMsg["OrchestrationMessage"] = new EnumValue<OrchestrationMessage>(msgFlags);
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[14628] | 61 | var problem = new MaximizationVariegationProblem<RealVectorEncoding>();
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[14616] | 62 | problem.Encoding.Length = TspParameter.Value.Coordinates.Rows * 2;
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| 63 | problem.Encoding.Bounds = new DoubleMatrix(new[,] { { -1.0, 1.0 } });
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| 64 | metaMsg["Problem"] = problem;
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| 65 | MetaSolverOrchestrationPort.SendMessage(metaMsg);
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| 66 | }
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| 67 |
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[14601] | 68 | #region MetaSolver Message Handling
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[14610] | 69 | protected override void MetaSolverEvaluationPortMessage(IMessage message) {
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[14601] | 70 | var factors = (RealVector)message["RealVector"];
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| 71 |
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| 72 | var tsp = (TravelingSalesmanProblem)TspParameter.Value.Clone();
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[14604] | 73 | for (int i = 0; i < tsp.Coordinates.Rows; i++) {
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[14601] | 74 | tsp.Coordinates[i, 0] = (int)Math.Ceiling(tsp.Coordinates[i, 0] * factors[i * 2]);
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| 75 | tsp.Coordinates[i, 1] = (int)Math.Ceiling(tsp.Coordinates[i, 1] * factors[i * 2 + 1]);
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| 76 | }
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[14653] | 77 | tsp.DistanceMatrix = new DistanceMatrix(TtpUtils.GetDistances(tsp.Coordinates, distanceType));
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[14601] | 78 |
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| 79 | var tspMsg = TspSolverOrchestrationPort.PrepareMessage();
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[14610] | 80 | tspMsg["OrchestrationMessage"] = new EnumValue<OrchestrationMessage>(OrchestrationMessage.Prepare | OrchestrationMessage.ClearRuns | OrchestrationMessage.Start);
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[14601] | 81 | tspMsg["Problem"] = tsp;
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| 82 | TspSolverOrchestrationPort.SendMessage(tspMsg);
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| 83 | cts.Token.ThrowIfCancellationRequested();
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| 84 |
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[14628] | 85 | var tspResults = (ResultCollection)tspMsg["Results"];
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[14604] | 86 | var bestTspSolution = (PathTSPTour)tspResults["Best TSP Solution"].Value.Clone();
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[14601] | 87 | var coordinates = (DoubleMatrix)TspParameter.Value.Coordinates.Clone();
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| 88 | var tour = new PathTSPTour(coordinates, bestTspSolution.Permutation, new DoubleValue(TSPCoordinatesPathEvaluator.Apply(new TSPEuclideanPathEvaluator(), coordinates, bestTspSolution.Permutation)));
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| 89 |
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[14653] | 90 | var availability = TtpUtils.GetAvailability(AvailabilityParameter.Value.ToArray());
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| 91 |
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[14601] | 92 | var kspMsg = KspSolverOrchestrationPort.PrepareMessage();
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[14610] | 93 | kspMsg["OrchestrationMessage"] = new EnumValue<OrchestrationMessage>(OrchestrationMessage.Prepare | OrchestrationMessage.ClearRuns | OrchestrationMessage.Start);
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[14601] | 94 | var lpp = new LootProfitProblem {
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| 95 | Tsp = (TravelingSalesmanProblem)TspParameter.Value.Clone(),
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| 96 | Ksp = (BinaryKnapsackProblem)KspParameter.Value.Clone(),
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| 97 | FixedTspSolution = bestTspSolution.Permutation,
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[14653] | 98 | Availability = availability,
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[14601] | 99 | RentingRatio = RentingRatioParameter.Value.Value,
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| 100 | MinSpeed = MinSpeedParameter.Value.Value,
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[14604] | 101 | MaxSpeed = MaxSpeedParameter.Value.Value,
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[14601] | 102 | };
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| 103 | lpp.Encoding.Length = KspParameter.Value.Length;
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| 104 | kspMsg["Problem"] = lpp;
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| 105 | KspSolverOrchestrationPort.SendMessage(kspMsg);
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| 106 | cts.Token.ThrowIfCancellationRequested();
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| 107 |
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[14628] | 108 | var kspResults = (ResultCollection)kspMsg["Results"];
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[14604] | 109 | var bestKspSolution = (BinaryVector)kspResults["Best Solution"].Value.Clone();
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[14601] | 110 | var kspCapacity = (IntValue)KspParameter.Value.KnapsackCapacity.Clone();
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| 111 | var kspPenalty = new DoubleValue(0.0);
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| 112 | var kspWeights = (IntArray)KspParameter.Value.Weights.Clone();
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| 113 | var kspValues = (IntArray)KspParameter.Value.Values.Clone();
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| 114 | var bestKspQuality = KnapsackEvaluator.Apply(bestKspSolution, kspCapacity, kspPenalty, kspWeights, kspValues).Quality;
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| 115 | var loot = new KnapsackSolution(bestKspSolution, bestKspQuality, kspCapacity, kspWeights, kspValues);
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| 116 |
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| 117 | #region Analyze
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[14604] | 118 | double objectiveValue = TtpUtils.Evaluate(TspParameter.Value, tour.Permutation.ToArray(), KspParameter.Value, loot.BinaryVector.ToArray(),
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[14653] | 119 | availability, RentingRatioParameter.Value.Value, MinSpeedParameter.Value.Value, MaxSpeedParameter.Value.Value);
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[14601] | 120 | ((DoubleValue)message["Quality"]).Value = objectiveValue;
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| 121 |
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| 122 | IResult bestQuality;
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| 123 | if (!Results.TryGetValue("Best TTP Quality", out bestQuality)) {
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| 124 | Results.Add(new Result("Best TTP Quality", new DoubleValue(objectiveValue)));
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| 125 | Results.Add(new Result("Best Tour", tour));
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| 126 | Results.Add(new Result("Best Loot", loot));
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[14610] | 127 | } else if (objectiveValue > ((DoubleValue)bestQuality.Value).Value) {
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[14601] | 128 | ((DoubleValue)bestQuality.Value).Value = objectiveValue;
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| 129 | Results["Best Tour"].Value = tour;
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| 130 | Results["Best Loot"].Value = loot;
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| 131 | }
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| 132 | #endregion
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| 133 | }
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| 134 | #endregion
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| 135 | }
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| 136 | }
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