1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2014 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 HeuristicLab.Common;
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23 | using HeuristicLab.Core;
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24 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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25 | using HeuristicLab.Data;
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26 |
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27 | namespace HeuristicLab.Algorithms.ParticleSwarmOptimization {
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28 | [Item("Von Neumann Topology Initializer", "Every particle is connected with the two following and the two previous particles wrapping around at the beginning and the end of the population.")]
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29 | [StorableClass]
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30 | public sealed class VonNeumannTopologyInitializer : TopologyInitializer {
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31 |
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32 | #region Construction & Cloning
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33 |
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34 | [StorableConstructor]
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35 | private VonNeumannTopologyInitializer(bool deserializing) : base(deserializing) { }
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36 | private VonNeumannTopologyInitializer(VonNeumannTopologyInitializer original, Cloner cloner) : base(original, cloner) { }
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37 | public VonNeumannTopologyInitializer() : base() { }
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38 |
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39 | public override IDeepCloneable Clone(Cloner cloner) {
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40 | return new VonNeumannTopologyInitializer(this, cloner);
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41 | }
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42 |
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43 | #endregion
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44 |
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45 | public override IOperation Apply() {
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46 | ItemArray<IntArray> neighbors = new ItemArray<IntArray>(SwarmSize);
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47 | for (int i = 0; i < SwarmSize; i++) {
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48 | neighbors[i] = new IntArray(new[] {
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49 | (SwarmSize + i-2) % SwarmSize,
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50 | (SwarmSize + i-1) % SwarmSize,
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51 | (i+1) % SwarmSize,
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52 | (i+2) % SwarmSize
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53 | });
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54 | }
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55 | Neighbors = neighbors;
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56 | return base.Apply();
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57 | }
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58 | }
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59 | }
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