#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 System.Linq; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Permutation; using HeuristicLab.Evolutionary; using HeuristicLab.Operators; using HeuristicLab.Routing.TSP; using HeuristicLab.Logging; using System.Diagnostics; using HeuristicLab.Selection; using System.Threading; using System.IO; using HeuristicLab.Random; namespace HeuristicLab.FixedOperators { class FixedSGAMain : FixedOperatorBase { public override string Description { get { return @"Implements the functionality of SGAMain with fixed control structures. Operators like selection, crossover, mutation and evaluation are delegated."; } } // Shared protected Sorter sorter; // CreateChildren protected Counter counter; protected IRandom random; protected DoubleData probability; protected ChildrenInitializer ci; protected OperatorBase crossover; protected OperatorBase mutator; protected OperatorBase evaluator; protected SubScopesRemover sr; protected StochasticBranch sb; protected OperatorBase selector; // CreateReplacement protected LeftSelector ls; protected RightReducer rr; protected RightSelector rs; protected LeftReducer lr; protected MergingReducer mr; //long[] timesExecuteCreateChildren; public FixedSGAMain() : base() { AddVariableInfo(new VariableInfo("Selector", "Selection strategy for SGA", typeof(OperatorBase), VariableKind.In)); AddVariableInfo(new VariableInfo("MaximumGenerations", "Maximum number of generations to create", typeof(IntData), VariableKind.In)); AddVariableInfo(new VariableInfo("Generations", "Number of processed generations", typeof(IntData), VariableKind.In | VariableKind.Out)); Name = "FixedSGAMain"; sorter = new Sorter(); sorter.GetVariableInfo("Descending").ActualName = "Maximization"; sorter.GetVariableInfo("Value").ActualName = "Quality"; InitCreateChildren(); InitReplacement(); sb = new StochasticBranch(); sb.GetVariableInfo("Probability").ActualName = "MutationRate"; } private void InitReplacement() { ls = new LeftSelector(); rr = new RightReducer(); rs = new RightSelector(); lr = new LeftReducer(); mr = new MergingReducer(); ls.GetVariableInfo("Selected").ActualName = "Elites"; rs.GetVariableInfo("Selected").ActualName = "Elites"; } private void InitCreateChildren() { // variables for create children ci = new ChildrenInitializer(); // variables infos AddVariableInfo(new VariableInfo("Random", "Pseudo random number generator", typeof(IRandom), VariableKind.In)); AddVariableInfo(new VariableInfo("MutationRate", "Probability to choose first branch", typeof(DoubleData), VariableKind.In)); AddVariableInfo(new VariableInfo("Crossover", "Crossover strategy for SGA", typeof(OperatorBase), VariableKind.In)); AddVariableInfo(new VariableInfo("Mutator", "Mutation strategy for SGA", typeof(OperatorBase), VariableKind.In)); AddVariableInfo(new VariableInfo("Evaluator", "Evaluation strategy for SGA", typeof(OperatorBase), VariableKind.In)); sr = new SubScopesRemover(); sr.GetVariableInfo("SubScopeIndex").Local = true; counter = new Counter(); counter.GetVariableInfo("Value").ActualName = "EvaluatedSolutions"; } public override IOperation Apply(IScope scope) { base.Apply(scope); Stopwatch swApply = new Stopwatch(); swApply.Start(); #region Initialization QualityLogger ql = new QualityLogger(); BestAverageWorstQualityCalculator bawqc = new BestAverageWorstQualityCalculator(); DataCollector dc = new DataCollector(); ItemList names = dc.GetVariable("VariableNames").GetValue>(); names.Add(new StringData("BestQuality")); names.Add(new StringData("AverageQuality")); names.Add(new StringData("WorstQuality")); LinechartInjector lci = new LinechartInjector(); lci.GetVariableInfo("Linechart").ActualName = "Quality Linechart"; lci.GetVariable("NumberOfLines").GetValue().Data = 3; IntData maxGenerations = GetVariableValue("MaximumGenerations", scope, true); IntData nrOfGenerations = GetVariableValue("Generations", scope, true); IntData subscopeNr; try { subscopeNr = scope.GetVariableValue("SubScopeNr", false); } catch (Exception) { subscopeNr = new IntData(0); scope.AddVariable(new Variable("SubScopeNr", subscopeNr)); } ci = new ChildrenInitializer(); GetOperatorsFromScope(scope); try { sb.RemoveSubOperator(0); } catch (Exception) { } sb.AddSubOperator(mutator); IScope s; IScope s2; #endregion try { for (; nrOfGenerations.Data < maxGenerations.Data; nrOfGenerations.Data++) { Execute(selector, scope); ////// Create Children ////// // ChildrenInitializer s = scope.SubScopes[1]; Execute(ci, s); SaveExecutionPointer(); // UniformSequentialSubScopesProcessor for (; subscopeNr.Data < s.SubScopes.Count; subscopeNr.Data++) { SetExecutionPointerToLastSaved(); s2 = s.SubScopes[subscopeNr.Data]; Execute(crossover, s2); // Stochastic Branch Execute(sb, s2); // ganz böse!!!!!!! // wird nach dem stochastic branch angehalten und später fortgesetzt, // wird eine Zufallszahl erzeugt, die aber nicht verwendet wird. // Dadurch kommt der GA auf ein anderes Endergebnis // Lösung: Stochastic Branch Operator verwenden //randomNumber = random.NextDouble(); //output.AppendLine(randomNumber.ToString()); //if (randomNumber < probability.Data) // Execute(mutator, s2); //else // Execute(empty, s2); Execute(evaluator, s2); Execute(sr, s2); Execute(counter, s2); } // foreach Execute(sorter, s); ////// END Create Children ////// DoReplacement(scope); Execute(ql, scope); Execute(bawqc, scope); Execute(dc, scope); Execute(lci, scope); subscopeNr.Data = 0; ResetExecutionPointer(); } // for i //TextWriter tw = new StreamWriter(DateTime.Now.ToFileTime() + ".txt"); //tw.Write(output.ToString()); //tw.Close(); //output = new StringBuilder(); swApply.Stop(); Console.WriteLine("SGAMain.Apply(): {0}", swApply.Elapsed); } // try catch (CancelException) { Console.WriteLine("Micro engine aborted by cancel flag."); return new AtomicOperation(this, scope); } return null; } // Apply /// /// Fetch main operators like selector, crossover, mutator, ... from scope /// and store them in instance variables. /// /// protected void GetOperatorsFromScope(IScope scope) { selector = (OperatorBase)GetVariableValue("Selector", scope, true); crossover = (OperatorBase)GetVariableValue("Crossover", scope, true); mutator = (OperatorBase)GetVariableValue("Mutator", scope, true); evaluator = GetVariableValue("Evaluator", scope, true); random = GetVariableValue("Random", scope, true); probability = GetVariableValue("MutationRate", scope, true); } /// /// /// /// protected void CreateChildren(IScope scope) { // ChildrenInitializer Execute(ci, scope); // UniformSequentialSubScopesProcessor foreach (IScope s in scope.SubScopes) { Execute(crossover, s); // Stochastic Branch if (random.NextDouble() < probability.Data) Execute(mutator, s); Execute(evaluator, s); Execute(sr, s); Execute(counter, s); } // foreach Execute(sorter, scope); } // CreateChildren protected void DoReplacement(IScope scope) { //// SequentialSubScopesProcessor Execute(ls, scope.SubScopes[0]); Execute(rr, scope.SubScopes[0]); Execute(rs, scope.SubScopes[1]); Execute(lr, scope.SubScopes[1]); Execute(mr, scope); Execute(sorter, scope); } // DoReplacement } // class FixedSGAMain } // namespace HeuristicLab.FixedOperators