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source: branches/OptimizationNetworks/HeuristicLab.Networks.IntegratedOptimization.TravelingThief/3.3/Problems/LootProfitProblem.cs @ 14610

Last change on this file since 14610 was 14610, checked in by jkarder, 7 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: 3.5 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.Collections.Generic;
23using System.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Encodings.BinaryVectorEncoding;
27using HeuristicLab.Encodings.PermutationEncoding;
28using HeuristicLab.Optimization;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Problems.Binary;
31using HeuristicLab.Problems.TravelingSalesman;
32
33namespace HeuristicLab.Networks.IntegratedOptimization.TravelingThief {
34  [Item("Loot Profit Problem", "Represents a problem whose objective is to optimize a TTP loot for fixed TTP tour.")]
35  [Creatable(CreatableAttribute.Categories.Problems, Priority = 999)]
36  [StorableClass]
37  public class LootProfitProblem : BinaryProblem {
38    public override bool Maximization {
39      get { return true; }
40    }
41
42    [Storable]
43    public TravelingSalesmanProblem Tsp { get; set; }
44    [Storable]
45    public BinaryKnapsackProblem Ksp { get; set; }
46    [Storable]
47    public Permutation FixedTspSolution { get; set; }
48    [Storable]
49    public int[] Availability { get; set; }
50    [Storable]
51    public double RentingRatio { get; set; }
52    [Storable]
53    public double MinSpeed { get; set; }
54    [Storable]
55    public double MaxSpeed { get; set; }
56    [Storable]
57    public TtpUtils.DistanceType DistanceType { get; set; }
58
59    [StorableConstructor]
60    protected LootProfitProblem(bool deserializing) : base(deserializing) { }
61    protected LootProfitProblem(LootProfitProblem original, Cloner cloner) : base(original, cloner) {
62      Tsp = cloner.Clone(original.Tsp);
63      Ksp = cloner.Clone(original.Ksp);
64      FixedTspSolution = cloner.Clone(original.FixedTspSolution);
65      Availability = original.Availability != null ? (int[])original.Availability.Clone() : null;
66      RentingRatio = original.RentingRatio;
67      MinSpeed = original.MinSpeed;
68      MaxSpeed = original.MaxSpeed;
69      DistanceType = original.DistanceType;
70    }
71    public LootProfitProblem() : base() {
72      Encoding.Length = 5;
73    }
74
75    public override IDeepCloneable Clone(Cloner cloner) {
76      return new LootProfitProblem(this, cloner);
77    }
78
79    public override double Evaluate(BinaryVector vector, IRandom random) {
80      return TtpUtils.Evaluate(Tsp, FixedTspSolution.ToArray(),
81                                  Ksp, vector.ToArray(),
82                                  Availability, RentingRatio, MinSpeed, MaxSpeed, DistanceType);
83    }
84
85    public override IEnumerable<Individual> GetNeighbors(Individual individual, IRandom random) {
86      while (true) {
87        var neighbor = individual.Copy();
88        SinglePositionBitflipManipulator.Apply(random, neighbor.BinaryVector());
89        yield return neighbor;
90      }
91    }
92  }
93}
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