#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 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 HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HEAL.Attic;
namespace HeuristicLab.Problems.TestFunctions {
///
/// An operator that improves test functions solutions.
///
///
/// It is implemented as described in Laguna, M. and Martí, R. (2003). Scatter Search: Methodology and Implementations in C. Operations Research/Computer Science Interfaces Series, Vol. 24. Springer.
/// The operator uses an implementation of the Nelder-Mead method with adaptive parameters as described in Gao, F. and Han, L. (2010). Implementing the Nelder-Mead simplex algorithm with adaptive parameters. Computational Optimization and Applications, Vol. 51. Springer. and conducts relection, expansion, contraction and reduction on the test functions solution.
///
[Item("SingleObjectiveTestFunctionImprovementOperator", "An operator that improves test functions solutions. It is implemented as described in Laguna, M. and Martí, R. (2003). Scatter Search: Methodology and Implementations in C. Operations Research/Computer Science Interfaces Series, Vol. 24. Springer.")]
[StorableType("4F33884D-D763-4F3A-9DC1-F3DF8EF7F48E")]
public sealed class SingleObjectiveTestFunctionImprovementOperator : SingleSuccessorOperator, ISingleObjectiveImprovementOperator {
#region Parameter properties
public IValueParameter AlphaParameter {
get { return (IValueParameter)Parameters["Alpha"]; }
}
public IValueParameter BetaParameter {
get { return (IValueParameter)Parameters["Beta"]; }
}
public IValueLookupParameter BoundsParameter {
get { return (IValueLookupParameter)Parameters["Bounds"]; }
}
public ScopeParameter CurrentScopeParameter {
get { return (ScopeParameter)Parameters["CurrentScope"]; }
}
public IValueParameter DeltaParameter {
get { return (IValueParameter)Parameters["Delta"]; }
}
public IValueLookupParameter EvaluatorParameter {
get { return (IValueLookupParameter)Parameters["Evaluator"]; }
}
public IValueParameter GammaParameter {
get { return (IValueParameter)Parameters["Gamma"]; }
}
public IValueLookupParameter ImprovementAttemptsParameter {
get { return (IValueLookupParameter)Parameters["ImprovementAttempts"]; }
}
public IValueLookupParameter SolutionParameter {
get { return (IValueLookupParameter)Parameters["Solution"]; }
}
#endregion
#region Properties
private DoubleValue Alpha {
get { return AlphaParameter.Value; }
}
private DoubleValue Beta {
get { return BetaParameter.Value; }
}
private DoubleMatrix Bounds {
get { return BoundsParameter.ActualValue; }
}
public IScope CurrentScope {
get { return CurrentScopeParameter.ActualValue; }
}
private DoubleValue Delta {
get { return DeltaParameter.Value; }
}
public ISingleObjectiveTestFunctionProblemEvaluator Evaluator {
get { return EvaluatorParameter.ActualValue; }
}
private DoubleValue Gamma {
get { return GammaParameter.Value; }
}
public IntValue ImprovementAttempts {
get { return ImprovementAttemptsParameter.ActualValue; }
}
#endregion
[StorableConstructor]
private SingleObjectiveTestFunctionImprovementOperator(StorableConstructorFlag _) : base(_) { }
private SingleObjectiveTestFunctionImprovementOperator(SingleObjectiveTestFunctionImprovementOperator original, Cloner cloner) : base(original, cloner) { }
public SingleObjectiveTestFunctionImprovementOperator()
: base() {
#region Create parameters
Parameters.Add(new ValueParameter("Alpha", new DoubleValue(1.0)));
Parameters.Add(new ValueParameter("Beta", new DoubleValue(2.0)));
Parameters.Add(new ValueLookupParameter("Bounds", "The lower and upper bounds in each dimension."));
Parameters.Add(new ScopeParameter("CurrentScope", "The current scope that contains the solution to be improved."));
Parameters.Add(new ValueParameter("Delta", new DoubleValue(0.5)));
Parameters.Add(new ValueLookupParameter("Evaluator", "The operator used to evaluate solutions."));
Parameters.Add(new ValueParameter("Gamma", new DoubleValue(0.5)));
Parameters.Add(new ValueLookupParameter("ImprovementAttempts", "The number of improvement attempts the operator should perform.", new IntValue(100)));
Parameters.Add(new ValueLookupParameter("Solution", "The solution to be improved. This parameter is used for name translation only."));
#endregion
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SingleObjectiveTestFunctionImprovementOperator(this, cloner);
}
public override IOperation Apply() {
RealVector bestSol = CurrentScope.Variables[SolutionParameter.ActualName].Value as RealVector;
if (bestSol == null)
throw new ArgumentException("Cannot improve solution because it has the wrong type.");
var evaluator = Evaluator;
double bestSolQuality = evaluator.Evaluate(bestSol);
// create perturbed solutions
RealVector[] simplex = new RealVector[bestSol.Length];
for (int i = 0; i < simplex.Length; i++) {
simplex[i] = bestSol.Clone() as RealVector;
simplex[i][i] += 0.1 * (Bounds[0, 1] - Bounds[0, 0]);
if (simplex[i][i] > Bounds[0, 1]) simplex[i][i] = Bounds[0, 1];
if (simplex[i][i] < Bounds[0, 0]) simplex[i][i] = Bounds[0, 0];
}
// improve solutions
for (int i = 0; i < ImprovementAttempts.Value; i++) {
// order according to their objective function value
Array.Sort(simplex, (x, y) => evaluator.Evaluate(x).CompareTo(evaluator.Evaluate(y)));
// calculate centroid
RealVector centroid = new RealVector(bestSol.Length);
foreach (var vector in simplex)
for (int j = 0; j < centroid.Length; j++)
centroid[j] += vector[j];
for (int j = 0; j < centroid.Length; j++)
centroid[j] /= simplex.Length;
// reflection
RealVector reflectionPoint = new RealVector(bestSol.Length);
for (int j = 0; j < reflectionPoint.Length; j++)
reflectionPoint[j] = centroid[j] + Alpha.Value * (centroid[j] - simplex[simplex.Length - 1][j]);
double reflectionPointQuality = evaluator.Evaluate(reflectionPoint);
if (evaluator.Evaluate(simplex[0]) <= reflectionPointQuality
&& reflectionPointQuality < evaluator.Evaluate(simplex[simplex.Length - 2]))
simplex[simplex.Length - 1] = reflectionPoint;
// expansion
if (reflectionPointQuality < evaluator.Evaluate(simplex[0])) {
RealVector expansionPoint = new RealVector(bestSol.Length);
for (int j = 0; j < expansionPoint.Length; j++)
expansionPoint[j] = centroid[j] + Beta.Value * (reflectionPoint[j] - centroid[j]);
simplex[simplex.Length - 1] = evaluator.Evaluate(expansionPoint) < reflectionPointQuality ? expansionPoint : reflectionPoint;
}
// contraction
if (evaluator.Evaluate(simplex[simplex.Length - 2]) <= reflectionPointQuality
&& reflectionPointQuality < evaluator.Evaluate(simplex[simplex.Length - 1])) {
RealVector outsideContractionPoint = new RealVector(bestSol.Length);
for (int j = 0; j < outsideContractionPoint.Length; j++)
outsideContractionPoint[j] = centroid[j] + Gamma.Value * (reflectionPoint[j] - centroid[j]);
if (evaluator.Evaluate(outsideContractionPoint) <= reflectionPointQuality) {
simplex[simplex.Length - 1] = outsideContractionPoint;
if (evaluator.Evaluate(reflectionPoint) >= evaluator.Evaluate(simplex[simplex.Length - 1])) {
RealVector insideContractionPoint = new RealVector(bestSol.Length);
for (int j = 0; j < insideContractionPoint.Length; j++)
insideContractionPoint[j] = centroid[j] - Gamma.Value * (reflectionPoint[j] - centroid[j]);
if (evaluator.Evaluate(insideContractionPoint) < evaluator.Evaluate(simplex[simplex.Length - 1])) simplex[simplex.Length - 1] = insideContractionPoint;
}
}
}
// reduction
for (int j = 1; j < simplex.Length; j++)
for (int k = 0; k < simplex[j].Length; k++)
simplex[j][k] = simplex[0][k] + Delta.Value * (simplex[j][k] - simplex[0][k]);
}
for (int i = 0; i < simplex[0].Length; i++) {
if (simplex[0][i] > Bounds[0, 1]) simplex[0][i] = Bounds[0, 1];
if (simplex[0][i] < Bounds[0, 0]) simplex[0][i] = Bounds[0, 0];
}
CurrentScope.Variables[SolutionParameter.ActualName].Value = simplex[0];
CurrentScope.Variables.Add(new Variable("LocalEvaluatedSolutions", ImprovementAttempts));
return base.Apply();
}
}
}