#region License Information /* HeuristicLab * Copyright (C) 2002-2016 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 . */ #endregion using System.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Algorithms.ParticleSwarmOptimization { [Item("Random Topology Initializer", "Randomly connectes every particle with k other particles.")] [StorableClass] public sealed class RandomTopologyInitializer : TopologyInitializer { #region Parameters public ILookupParameter RandomParameter { get { return (ILookupParameter)Parameters["Random"]; } } public IValueLookupParameter NrOfConnectionsParameter { get { return (IValueLookupParameter)Parameters["NrOfConnections"]; } } #endregion #region Parameter Values private IRandom Random { get { return RandomParameter.ActualValue; } } private int NrOfConnections { get { return NrOfConnectionsParameter.ActualValue.Value; } } #endregion #region Construction & Cloning [StorableConstructor] private RandomTopologyInitializer(bool deserializing) : base(deserializing) { } private RandomTopologyInitializer(RandomTopologyInitializer original, Cloner cloner) : base(original, cloner) { } public RandomTopologyInitializer() { Parameters.Add(new LookupParameter("Random", "A random number generation.")); Parameters.Add(new ValueLookupParameter("NrOfConnections", "Nr of connected neighbors.", new IntValue(3))); } public override IDeepCloneable Clone(Cloner cloner) { return new RandomTopologyInitializer(this, cloner); } #endregion public override IOperation Apply() { ItemArray neighbors = new ItemArray(SwarmSize); for (int i = 0; i < SwarmSize; i++) { var numbers = Enumerable.Range(0, SwarmSize).ToList(); numbers.RemoveAt(i); var selectedNumbers = new List(NrOfConnections); for (int j = 0; j < NrOfConnections && numbers.Count > 0; j++) { int index = Random.Next(numbers.Count); selectedNumbers.Add(numbers[index]); numbers.RemoveAt(index); } neighbors[i] = new IntArray(selectedNumbers.ToArray()); } Neighbors = neighbors; return base.Apply(); } } }