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# source:trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/SumSquaresEvaluator.cs@3318

Last change on this file since 3318 was 3318, checked in by abeham, 14 years ago

Updated test functions, added reference for Zakharov
Did not find a reference for SumSquares, just described it
Added wiring for rastrigin and sphere
#934

File size: 3.4 KB
Line
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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
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 System;
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    /// <summary>
36    /// Returns false as the Sum Squares function is a minimization problem.
37    /// </summary>
38    public override bool Maximization {
39      get { return false; }
40    }
41    /// <summary>
42    /// Gets the optimum function value (0).
43    /// </summary>
44    public override double BestKnownQuality {
45      get { return 0; }
46    }
47    /// <summary>
48    /// Gets the lower and upper bound of the function.
49    /// </summary>
50    public override DoubleMatrix Bounds {
51      get { return new DoubleMatrix(new double[,] { { -10, 10 } }); }
52    }
53    /// <summary>
54    /// Gets the minimum problem size (1).
55    /// </summary>
56    public override int MinimumProblemSize {
57      get { return 1; }
58    }
59    /// <summary>
60    /// Gets the (theoretical) maximum problem size (2^31 - 1).
61    /// </summary>
62    public override int MaximumProblemSize {
63      get { return int.MaxValue; }
64    }
65
66    /// <summary>
67    /// Evaluates the test function for a specific <paramref name="point"/>.
68    /// </summary>
69    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
70    /// <returns>The result value of the Sum Squares function at the given point.</returns>
71    public static double Apply(RealVector point) {
72      double result = 0;
73      for (int i = 0; i < point.Length; i++) {
74        result += (i + 1) * point[i] * point[i];
75      }
76      return result;
77    }
78
79    /// <summary>
80    /// Evaluates the test function for a specific <paramref name="point"/>.
81    /// </summary>
82    /// <remarks>Calls <see cref="Apply"/>.</remarks>
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    protected override double EvaluateFunction(RealVector point) {
86      return Apply(point);
87    }
88  }
89}
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