source: stable/HeuristicLab.Algorithms.ParticleSwarmOptimization/3.3/RingTopologyInitializer.cs @ 13321

Last change on this file since 13321 was 12009, checked in by ascheibe, 8 years ago

#2212 updated copyright year

File size: 2.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
25using HeuristicLab.Data;
26
27namespace HeuristicLab.Algorithms.ParticleSwarmOptimization {
28  [Item("Ring Topology Initializer", "Connected every particle with its preceeding and its following particle.")]
29  [StorableClass]
30  public sealed class RingTopologyInitializer : TopologyInitializer {
31    #region Construction & Cloning
32
33    [StorableConstructor]
34    private RingTopologyInitializer(bool deserializing) : base(deserializing) { }
35    private RingTopologyInitializer(RingTopologyInitializer original, Cloner cloner) : base(original, cloner) { }
36    public RingTopologyInitializer() : base() { }
37
38    public override IDeepCloneable Clone(Cloner cloner) {
39      return new RingTopologyInitializer(this, cloner);
40    }
41
42    #endregion
43
44    public override IOperation Apply() {
45      ItemArray<IntArray> neighbors = new ItemArray<IntArray>(SwarmSize);
46      for (int i = 0; i < SwarmSize; i++) {
47        neighbors[i] = new IntArray(new[] { (SwarmSize + i - 1) % SwarmSize, (i + 1) % SwarmSize });
48      }
49      Neighbors = neighbors;
50      return base.Apply();
51    }
52  }
53}
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