#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();
}
}
}