source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/SumSquaresEvaluator.cs @ 12012

Last change on this file since 12012 was 12012, checked in by ascheibe, 5 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 4.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Encodings.RealVectorEncoding;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Problems.TestFunctions {
29  /// <summary>
30  /// The Sum Squares function is defined as sum(i * x_i * x_i) for i = 1..n
31  /// </summary>
32  [Item("SumSquaresEvaluator", "Evaluates the sum squares function on a given point. The optimum of this function is 0 at the origin. The Sum Squares function is defined as sum(i * x_i * x_i) for i = 1..n.")]
33  [StorableClass]
34  public class SumSquaresEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
35    public override string FunctionName { get { return "SumSquares"; } }
36    /// <summary>
37    /// Returns false as the Sum Squares function is a minimization problem.
38    /// </summary>
39    public override bool Maximization {
40      get { return false; }
41    }
42    /// <summary>
43    /// Gets the optimum function value (0).
44    /// </summary>
45    public override double BestKnownQuality {
46      get { return 0; }
47    }
48    /// <summary>
49    /// Gets the lower and upper bound of the function.
50    /// </summary>
51    public override DoubleMatrix Bounds {
52      get { return new DoubleMatrix(new double[,] { { -10, 10 } }); }
53    }
54    /// <summary>
55    /// Gets the minimum problem size (1).
56    /// </summary>
57    public override int MinimumProblemSize {
58      get { return 1; }
59    }
60    /// <summary>
61    /// Gets the (theoretical) maximum problem size (2^31 - 1).
62    /// </summary>
63    public override int MaximumProblemSize {
64      get { return int.MaxValue; }
65    }
66
67    [StorableConstructor]
68    protected SumSquaresEvaluator(bool deserializing) : base(deserializing) { }
69    protected SumSquaresEvaluator(SumSquaresEvaluator original, Cloner cloner) : base(original, cloner) { }
70    public SumSquaresEvaluator() : base() { }
71
72    public override IDeepCloneable Clone(Cloner cloner) {
73      return new SumSquaresEvaluator(this, cloner);
74    }
75
76    public override RealVector GetBestKnownSolution(int dimension) {
77      return new RealVector(dimension);
78    }
79
80    /// <summary>
81    /// Evaluates the test function for a specific <paramref name="point"/>.
82    /// </summary>
83    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
84    /// <returns>The result value of the Sum Squares function at the given point.</returns>
85    public static double Apply(RealVector point) {
86      double result = 0;
87      for (int i = 0; i < point.Length; i++) {
88        result += (i + 1) * point[i] * point[i];
89      }
90      return result;
91    }
92
93    /// <summary>
94    /// Evaluates the test function for a specific <paramref name="point"/>.
95    /// </summary>
96    /// <remarks>Calls <see cref="Apply"/>.</remarks>
97    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
98    /// <returns>The result value of the Sum Squares function at the given point.</returns>
99    public override double Evaluate(RealVector point) {
100      return Apply(point);
101    }
102  }
103}
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