source: branches/SuccessProgressAnalysis/HeuristicLab.Problems.VehicleRouting/3.3/Encodings/General/Manipulators/BiasedMultiVRPSolutionManipulator.cs @ 5682

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2011 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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Common;
using HeuristicLab.Analysis;
using HeuristicLab.Parameters;
using HeuristicLab.Optimization;
using HeuristicLab.Data;
using HeuristicLab.Collections;

namespace HeuristicLab.Problems.VehicleRouting.Encodings.General {
  [Item("BiasedMultiVRPSolutionManipulator", "Randomly selects and applies one of its crossovers every time it is called based on the success progress.")]
  [StorableClass]
  public class BiasedMultiVRPSolutionManipulator : MultiVRPSolutionManipulator {
    public ValueLookupParameter<DoubleArray> ActualProbabilitiesParameter {
      get { return (ValueLookupParameter<DoubleArray>)Parameters["ActualProbabilities"]; }
    }

    public ValueLookupParameter<IntValue> LastUpdateParameter {
      get { return (ValueLookupParameter<IntValue>)Parameters["LastUpdate"]; }
    }
    
    public ValueLookupParameter<ResultCollection> ResultsParameter {
      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
    }

    public ValueLookupParameter<StringValue> SuccessProgressAnalyisis {
      get { return (ValueLookupParameter<StringValue>)Parameters["SuccessProgressAnalysis"]; }
    }

    public ValueLookupParameter<IntValue> Interval {
      get { return (ValueLookupParameter<IntValue>)Parameters["Interval"]; }
    }

    public ValueLookupParameter<DoubleValue> Factor {
      get { return (ValueLookupParameter<DoubleValue>)Parameters["Factor"]; }
    }

    public LookupParameter<IntValue> Generations {
      get { return (LookupParameter<IntValue>)Parameters["Generations"]; }
    }

    [StorableConstructor]
    protected BiasedMultiVRPSolutionManipulator(bool deserializing) : base(deserializing) { }
    protected BiasedMultiVRPSolutionManipulator(BiasedMultiVRPSolutionManipulator original, Cloner cloner) : base(original, cloner) { }
    public BiasedMultiVRPSolutionManipulator()
      : base() {
      Parameters.Add(new ValueLookupParameter<DoubleArray>("ActualProbabilities", "The array of relative probabilities for each operator."));
      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the succedd progress analysis results should be stored."));
      Parameters.Add(new ValueLookupParameter<StringValue>("SuccessProgressAnalysis", "The success progress analyisis to be considered", 
        new StringValue("Success Progress ExecutedMutationOperator")));
      Parameters.Add(new ValueLookupParameter<IntValue>("Interval", "The interval the probabilities should be updated", new IntValue(1)));
      Parameters.Add(new ValueLookupParameter<IntValue>("LastUpdate", "Specifies when the probabilities were last updated", new IntValue(0)));
      Parameters.Add(new ValueLookupParameter<DoubleValue>("Factor", "The factor with which the probabilities should be updated", new DoubleValue(35)));
      Parameters.Add(new LookupParameter<IntValue>("Generations", "The current number of generations."));
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new BiasedMultiVRPSolutionManipulator(this, cloner);
    }

    public override IOperation Apply() {
      int generations = Generations.ActualValue.Value;
      int interval = Interval.ActualValue.Value;

      if (generations == 0) {
        ActualProbabilitiesParameter.Value = ProbabilitiesParameter.ActualValue.Clone() as DoubleArray;
        LastUpdateParameter.Value = new IntValue(0);
      } else if (generations % interval == 0 && LastUpdateParameter.Value.Value != generations) {
        String key = SuccessProgressAnalyisis.ActualValue.Value;
        if (ResultsParameter.ActualValue != null && ResultsParameter.ActualValue.ContainsKey(key)) {
          DataTable successProgressAnalysis = ResultsParameter.ActualValue[key].Value as DataTable;

          for (int i = 0; i < Operators.Count; i++) {
            IOperator current = Operators[i];

            if (successProgressAnalysis.Rows.ContainsKey(current.Name)) {
              DataRow row = successProgressAnalysis.Rows[current.Name];

              double sum = 0.0;
              ObservableList<double> usages = row.Values;

              int end = generations;
              int start = generations - interval;

              if (end - start > 0) {
                for (int j = start; j < end; j++) {
                  sum += (double)usages[j];
                }

                ActualProbabilitiesParameter.Value[i] += ((sum / (end - start)) / ActualProbabilitiesParameter.Value[i]) * Factor.Value.Value;
              }
            }
          }
        }

        //normalize
        double max = ActualProbabilitiesParameter.Value.Max();
        for (int i = 0; i < ActualProbabilitiesParameter.Value.Length; i++) {
          ActualProbabilitiesParameter.Value[i] /= max;
        }

        LastUpdateParameter.Value.Value = generations;
      }

      ////////////////
      IRandom random = RandomParameter.ActualValue;
      DoubleArray probabilities = ActualProbabilitiesParameter.ActualValue;
      if (probabilities.Length != Operators.Count) {
        throw new InvalidOperationException(Name + ": The list of probabilities has to match the number of operators");
      }
      IOperator successor = null;
      var checkedOperators = Operators.CheckedItems;
      if (checkedOperators.Count() > 0) {
        // select a random operator from the checked operators
        double sum = (from indexedItem in checkedOperators select probabilities[indexedItem.Index]).Sum();
        if (sum == 0) throw new InvalidOperationException(Name + ": All selected operators have zero probability.");
        double r = random.NextDouble() * sum;
        sum = 0;
        foreach (var indexedItem in checkedOperators) {
          sum += probabilities[indexedItem.Index];
          if (sum > r) {
            successor = indexedItem.Value;
            break;
          }
        }
      }

      IOperation successorOp = null;
      if (Successor != null)
        successorOp = ExecutionContext.CreateOperation(Successor);
      OperationCollection next = new OperationCollection(successorOp);
      if (successor != null) {
        SelectedOperatorParameter.ActualValue = new StringValue(successor.GetType().Name);

        if (CreateChildOperation)
          next.Insert(0, ExecutionContext.CreateChildOperation(successor));
        else next.Insert(0, ExecutionContext.CreateOperation(successor));
      } else {
        SelectedOperatorParameter.ActualValue = new StringValue("");
      }

      return next;
    }
  }
}