source: branches/3043-Regression-Instances-For-Scaling/HeuristicLab.Algorithms.ParticleSwarmOptimization/3.3/VonNeumannTopologyInitializer.cs @ 17506

#region License Information
/* HeuristicLab
 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using HeuristicLab.Common;
using HeuristicLab.Core;
using HEAL.Attic;
using HeuristicLab.Data;

namespace HeuristicLab.Algorithms.ParticleSwarmOptimization {
  [Item("Von Neumann Topology Initializer", "Every particle is informed by the two following and the two previous particles wrapping around at the beginning and the end of the swarm (in addition each particle also informs itself).")]
  [StorableType("F1516EBD-DA8D-462E-94DD-44391191ED8A")]
  public sealed class VonNeumannTopologyInitializer : TopologyInitializer {

    #region Construction & Cloning

    [StorableConstructor]
    private VonNeumannTopologyInitializer(StorableConstructorFlag _) : base(_) { }
    private VonNeumannTopologyInitializer(VonNeumannTopologyInitializer original, Cloner cloner) : base(original, cloner) { }
    public VonNeumannTopologyInitializer() : base() { }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new VonNeumannTopologyInitializer(this, cloner);
    }

    #endregion

    public override IOperation Apply() {
      var swarmSize = SwarmSizeParameter.ActualValue.Value;

      ItemArray<IntArray> neighbors = new ItemArray<IntArray>(swarmSize);
      for (int i = 0; i < swarmSize; i++) {
        neighbors[i] = new IntArray(new[] {
          (swarmSize + i-2) % swarmSize,
          (swarmSize + i-1) % swarmSize,
          i,
          (i+1) % swarmSize,
          (i+2) % swarmSize
        });
      }
      NeighborsParameter.ActualValue = neighbors;
      return base.Apply();
    }
  }
}