#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 . */ #endregion using System; using System.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Encodings.RealVectorEncoding; using HeuristicLab.Optimization; using HEAL.Attic; using HeuristicLab.Problems.TestFunctions.MultiObjective; namespace HeuristicLab.Algorithms.MOCMAEvolutionStrategy { [Item("HypervolumeIndicator", "Selection of Offspring based on contributing Hypervolume")] [StorableType("ADF439D6-64E4-4C92-A4D3-E8C05B050406")] internal class HypervolumeIndicator : Item, IIndicator { #region Constructors and Cloning [StorableConstructor] protected HypervolumeIndicator(StorableConstructorFlag _) : base(_) { } protected HypervolumeIndicator(HypervolumeIndicator original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new HypervolumeIndicator(this, cloner); } public HypervolumeIndicator() { } #endregion public int LeastContributer(IReadOnlyList front, MultiObjectiveBasicProblem problem) { var frontCopy = front.Select(x => x.PenalizedFitness).ToList(); if (frontCopy.Count <= 1) return 0; var p = problem as MultiObjectiveTestFunctionProblem; var refPoint = BuildReferencePoint(p != null ? frontCopy.Concat(new[] { p.ReferencePoint.CloneAsArray() }) : frontCopy, problem.Maximization); var contributions = Enumerable.Range(0, frontCopy.Count).Select(i => Contribution(frontCopy, i, problem.Maximization, refPoint)); return contributions.Select((value, index) => new { value, index }).OrderBy(x => x.value).First().index; } #region Helpers private static double Contribution(IList front, int idx, bool[] maximization, double[] refPoint) { var point = front[idx]; front.RemoveAt(idx); var contribution = -Hypervolume.Calculate(front.ToArray(), refPoint, maximization); front.Insert(idx, point); return contribution; } private static double[] BuildReferencePoint(IEnumerable front, IReadOnlyList maximization) { var refPoint = new double[maximization.Count]; foreach (var point in front) for (var i = 0; i < maximization.Count; i++) refPoint[i] = maximization[i] ? Math.Min(refPoint[i], point[i]) : Math.Max(refPoint[i], point[i]); return refPoint; } #endregion } }