#region License Information /* HeuristicLab * Copyright (C) 2002-2008 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.Text; using HeuristicLab.Core; using HeuristicLab.Data; namespace HeuristicLab.Selection.OffspringSelection { public class OffspringSelector : OperatorBase { public override string Description { get { return @"TODO\r\nOperator description still missing ..."; } } public OffspringSelector() { AddVariableInfo(new VariableInfo("SuccessfulChild", "True if the child was successful", typeof(BoolData), VariableKind.In)); AddVariableInfo(new VariableInfo("SelectionPressureLimit", "Maximum selection pressure", typeof(DoubleData), VariableKind.In)); AddVariableInfo(new VariableInfo("SuccessRatioLimit", "Maximum success ratio", typeof(DoubleData), VariableKind.In)); AddVariableInfo(new VariableInfo("SelectionPressure", "Current selection pressure", typeof(DoubleData), VariableKind.New | VariableKind.Out)); AddVariableInfo(new VariableInfo("SuccessRatio", "Current success ratio", typeof(DoubleData), VariableKind.New | VariableKind.Out)); AddVariableInfo(new VariableInfo("GoodChildren", "Temporarily store successful children", typeof(ItemList), VariableKind.New | VariableKind.Out | VariableKind.In | VariableKind.Deleted)); AddVariableInfo(new VariableInfo("BadChildren", "Temporarily store unsuccessful children", typeof(ItemList), VariableKind.New | VariableKind.Out | VariableKind.In | VariableKind.Deleted)); } public override IOperation Apply(IScope scope) { double selectionPressureLimit = GetVariableValue("SelectionPressureLimit", scope, true).Data; double successRatioLimit = GetVariableValue("SuccessRatioLimit", scope, true).Data; IScope parents = scope.SubScopes[0]; IScope children = scope.SubScopes[1]; // retrieve good and bad children ItemList goodChildren = GetVariableValue("GoodChildren", scope, false, false); if (goodChildren == null) { goodChildren = new ItemList(); goodChildren.ItemType = typeof(IScope); IVariableInfo goodChildrenInfo = GetVariableInfo("GoodChildren"); if (goodChildrenInfo.Local) AddVariable(new Variable(goodChildrenInfo.ActualName, goodChildren)); else scope.AddVariable(new Variable(goodChildrenInfo.ActualName, goodChildren)); } ItemList badChildren = GetVariableValue("BadChildren", scope, false, false); if (badChildren == null) { badChildren = new ItemList(); badChildren.ItemType = typeof(IScope); IVariableInfo badChildrenInfo = GetVariableInfo("BadChildren"); if (badChildrenInfo.Local) AddVariable(new Variable(badChildrenInfo.ActualName, badChildren)); else scope.AddVariable(new Variable(badChildrenInfo.ActualName, badChildren)); } // separate new children in good and bad children IVariableInfo successfulInfo = GetVariableInfo("SuccessfulChild"); while (children.SubScopes.Count > 0) { IScope child = children.SubScopes[0]; bool successful = child.GetVariableValue(successfulInfo.ActualName, false).Data; if (successful) goodChildren.Add(child); else badChildren.Add(child); children.RemoveSubScope(child); } // calculate actual selection pressure and success ratio DoubleData selectionPressure = GetVariableValue("SelectionPressure", scope, false, false); if (selectionPressure == null) { IVariableInfo selectionPressureInfo = GetVariableInfo("SelectionPressure"); selectionPressure = new DoubleData(0); if (selectionPressureInfo.Local) AddVariable(new Variable(selectionPressureInfo.ActualName, selectionPressure)); else scope.AddVariable(new Variable(selectionPressureInfo.ActualName, selectionPressure)); } DoubleData successRatio = GetVariableValue("SuccessRatio", scope, false, false); if (successRatio == null) { IVariableInfo successRatioInfo = GetVariableInfo("SuccessRatio"); successRatio = new DoubleData(0); if (successRatioInfo.Local) AddVariable(new Variable(successRatioInfo.ActualName, successRatio)); else scope.AddVariable(new Variable(successRatioInfo.ActualName, successRatio)); } int goodCount = goodChildren.Count; int badCount = badChildren.Count; selectionPressure.Data = (goodCount + badCount) / ((double)parents.SubScopes.Count); successRatio.Data = goodCount / ((double)parents.SubScopes.Count); // check if enough children have been generated if (((selectionPressure.Data < selectionPressureLimit) && (successRatio.Data < successRatioLimit)) || ((goodCount + badCount) < parents.SubScopes.Count)) { // more children required -> reduce left and start children generation again scope.RemoveSubScope(parents); scope.RemoveSubScope(children); for (int i = 0; i < parents.SubScopes.Count; i++) scope.AddSubScope(parents.SubScopes[i]); return new AtomicOperation(SubOperators[0], scope); } else { // enough children generated while (children.SubScopes.Count < parents.SubScopes.Count) { if (goodChildren.Count > 0) { children.AddSubScope((IScope)goodChildren[0]); goodChildren.RemoveAt(0); } else { children.AddSubScope((IScope)badChildren[0]); badChildren.RemoveAt(0); } } // remove good and bad children again IVariableInfo goodChildrenInfo = GetVariableInfo("GoodChildren"); if (goodChildrenInfo.Local) RemoveVariable(goodChildrenInfo.ActualName); else scope.RemoveVariable(goodChildrenInfo.ActualName); IVariableInfo badChildrenInfo = GetVariableInfo("BadChildren"); if (badChildrenInfo.Local) RemoveVariable(badChildrenInfo.ActualName); else scope.RemoveVariable(badChildrenInfo.ActualName); return null; } } } }