[7686] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16710] | 3 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[7686] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Data;
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| 26 | using HeuristicLab.Optimization;
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| 27 | using HeuristicLab.Parameters;
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[16710] | 28 | using HEAL.Attic;
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[7686] | 29 | using HeuristicLab.Random;
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| 30 |
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| 31 | namespace HeuristicLab.Encodings.IntegerVectorEncoding {
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| 32 | /// <summary>
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| 33 | /// Manipulates each dimension in the integer vector with the mutation strength given
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| 34 | /// in the strategy parameter vector.
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| 35 | /// </summary>
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| 36 | [Item("SelfAdaptiveRoundedNormalAllPositionsManipulator", "This manipulation operator adds a value sigma_i * N(0,1) to the current value in each position i. The resulting value is rounded to the next feasible value. The values for sigma_i are looked up dynamically. If there are less elements in the strategy vector than positions, then the strategy vector is cycled.")]
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[16710] | 37 | [StorableType("2CD4AE6E-3A73-4514-AB66-4D94C700F779")]
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[8017] | 38 | public class SelfAdaptiveRoundedNormalAllPositionsManipulator : BoundedIntegerVectorManipulator, ISelfAdaptiveManipulator {
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[7686] | 39 | public Type StrategyParameterType {
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| 40 | get { return typeof(IIntegerVectorStdDevStrategyParameterOperator); }
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| 41 | }
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| 42 | /// <summary>
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| 43 | /// Parameter for the strategy vector.
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| 44 | /// </summary>
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| 45 | public ILookupParameter<DoubleArray> StrategyParameterParameter {
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| 46 | get { return (ILookupParameter<DoubleArray>)Parameters["StrategyParameter"]; }
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| 47 | }
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| 48 |
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| 49 | IParameter ISelfAdaptiveManipulator.StrategyParameterParameter {
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| 50 | get { return StrategyParameterParameter; }
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| 51 | }
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| 52 |
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| 53 | [StorableConstructor]
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[16710] | 54 | protected SelfAdaptiveRoundedNormalAllPositionsManipulator(StorableConstructorFlag _) : base(_) { }
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[7686] | 55 | protected SelfAdaptiveRoundedNormalAllPositionsManipulator(SelfAdaptiveRoundedNormalAllPositionsManipulator original, Cloner cloner) : base(original, cloner) { }
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| 56 | /// <summary>
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| 57 | /// Initializes a new instance of <see cref="SelfAdaptiveRoundedNormalAllPositionsManipulator"/> with one.
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| 58 | /// </summary>
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| 59 | public SelfAdaptiveRoundedNormalAllPositionsManipulator()
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| 60 | : base() {
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| 61 | Parameters.Add(new LookupParameter<DoubleArray>("StrategyParameter", "The vector containing the endogenous strategy parameters."));
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| 62 | }
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| 63 |
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| 64 | public override IDeepCloneable Clone(Cloner cloner) {
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| 65 | return new SelfAdaptiveRoundedNormalAllPositionsManipulator(this, cloner);
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| 66 | }
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| 67 |
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| 68 | /// <summary>
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| 69 | /// Performs an adaptive normally distributed all position manipulation on the given
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| 70 | /// <paramref name="vector"/> and rounding the results to the next feasible value.
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| 71 | /// </summary>
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| 72 | /// <exception cref="InvalidOperationException">Thrown when the strategy vector is not
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| 73 | /// as long as the vector to get manipulated.</exception>
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| 74 | /// <param name="strategyParameters">The strategy vector determining the strength of the mutation.</param>
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| 75 | /// <param name="random">A random number generator.</param>
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| 76 | /// <param name="vector">The integer vector to manipulate.</param>
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[8017] | 77 | /// <param name="bounds">The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).</param>
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[7686] | 78 | public static void Apply(IRandom random, IntegerVector vector, IntMatrix bounds, DoubleArray strategyParameters) {
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[8017] | 79 | if (strategyParameters == null || strategyParameters.Length == 0) throw new ArgumentException("SelfAdaptiveRoundedNormalAllPositionsManipulator: Vector containing the standard deviations is not defined.", "sigma");
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| 80 | if (bounds == null || bounds.Rows == 0 || bounds.Columns < 2) throw new ArgumentException("SelfAdaptiveRoundedNormalAllPositionsManipulator: Invalid bounds specified.", "bounds");
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[7686] | 81 | var N = new NormalDistributedRandom(random, 0.0, 1.0);
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| 82 | if (strategyParameters != null) {
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| 83 | for (int i = 0; i < vector.Length; i++) {
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| 84 | int min = bounds[i % bounds.Rows, 0], max = bounds[i % bounds.Rows, 1], step = 1;
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| 85 | if (bounds.Columns > 2) step = bounds[i % bounds.Rows, 2];
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| 86 |
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| 87 | int value = (vector[i] + (int)Math.Round((N.NextDouble() * strategyParameters[i % strategyParameters.Length])) - min) / step;
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[8790] | 88 | max = FloorFeasible(min, max, step, max - 1);
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[8017] | 89 | vector[i] = RoundFeasible(min, max, step, value);
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[7686] | 90 | }
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| 91 | }
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| 92 | }
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| 93 |
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| 94 | /// <summary>
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| 95 | /// Checks that the strategy vector is not null and forwards the call to the static Apply method.
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| 96 | /// </summary>
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| 97 | /// <param name="random">The random number generator.</param>
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| 98 | /// <param name="vector">The vector of integer values that is manipulated.</param>
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[8017] | 99 | /// <param name="bounds">The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).</param>
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| 100 | protected override void ManipulateBounded(IRandom random, IntegerVector vector, IntMatrix bounds) {
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| 101 | Apply(random, vector, bounds, StrategyParameterParameter.ActualValue);
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[7686] | 102 | }
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| 103 | }
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| 104 | }
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