[13350] | 1 | using System;
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| 2 | using System.Linq;
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| 3 | using System.Collections.Generic;
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| 4 | using HeuristicLab.Common;
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| 5 | using HeuristicLab.Core;
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| 6 | using HeuristicLab.Data;
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| 7 | using HeuristicLab.Optimization;
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| 8 | using HeuristicLab.Problems.Programmable;
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[13373] | 9 | //using HeuristicLab.Encodings.BinaryVectorEncoding;
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| 10 | //using HeuristicLab.Encodings.IntegerVectorEncoding;
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| 11 | //using HeuristicLab.Encodings.RealVectorEncoding;
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| 12 | //using HeuristicLab.Encodings.PermutationEncoding;
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| 13 | //using HeuristicLab.Encodings.LinearLinkageEncoding;
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[13350] | 14 |
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| 15 | namespace HeuristicLab.Problems.Programmable {
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[13373] | 16 | public class CompiledSingleObjectiveProblemDefinition : CompiledMultiObjectiveProblemDefinition<CombinedEncoding, CombinedSolution> {
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| 17 | public override bool[] Maximization { get { return new[] { true, false }; } }
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[13350] | 18 |
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| 19 | public override void Initialize() {
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| 20 | // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
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| 21 | // Define e.g. the length of the solution encoding or the solution creator by modifying the Encoding property
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| 22 | // Add additional initialization code e.g. private variables that you need for evaluating
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[13373] | 23 | //Encoding.Add(new BinaryVectorEncoding("b") { Length = 10 });
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[13390] | 24 | //Encoding.Add(new IntegerVectorEncoding("i") { Length = 10, Bounds = new IntMatrix(new int[,] { { -100, 100 } }) });
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| 25 | //Encoding.Add(new RealVectorEncoding("r") { Length = 10, Bounds = new DoubleMatrix(new double[,] { { -100, 100 } }) });
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| 26 | //Encoding.Add(new PermutationEncoding("p") { Length = 20, Type = PermutationTypes.Absolute });
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[13373] | 27 | //Encoding.Add(new LinearLinkageEncoding("lle") { Length = 30 });
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[13350] | 28 | }
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| 29 |
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[13373] | 30 | public override double[] Evaluate(CombinedSolution solution, IRandom random) {
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[13350] | 31 | // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
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| 32 | var quality = new[] { 0.0, 0.0 };
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[13390] | 33 | //var b = solution.GetSolution<BinaryVector>("b");
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| 34 | //quality[0] = b.Count(x => x); // one max!
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| 35 | //var r = solution.GetSolution<RealVector>("r");
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| 36 | //quality[1] = r.Select((i, v) => new { Idx = i, Val = v }).Sum(x => b[x.Idx] ? x.Val * x.Val : 0.0); // sphere
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[13373] | 37 |
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| 38 | // NOTE: Check the Maximization property above (true or false)!
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[13350] | 39 | return quality;
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| 40 | }
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| 41 |
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[13373] | 42 | public override void Analyze(CombinedSolution[] solutions, double[][] qualities, ResultCollection results, IRandom random) {
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[13350] | 43 | // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
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| 44 | // Write or update results given the range of vectors and resulting qualities
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[13373] | 45 | // Uncomment the following lines if you want to retrieve the best solution
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[13350] | 46 | }
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| 47 |
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[13373] | 48 | public override IEnumerable<CombinedSolution> GetNeighbors(CombinedSolution solution, IRandom random) {
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[13350] | 49 | // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
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| 50 | // Create new vectors, based on the given one that represent small changes
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| 51 | // This method is only called from move-based algorithms (Local Search, Simulated Annealing, etc.)
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| 52 | while (true) {
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| 53 | // Algorithm will draw only a finite amount of samples
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| 54 | // Change to a for-loop to return a concrete amount of neighbors
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[13373] | 55 | var neighbor = (CombinedSolution)solution.Clone();
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[13350] | 56 | // modify the solution specified as neighbor
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| 57 | yield return neighbor;
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| 58 | }
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| 59 | }
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| 60 |
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| 61 | // Implement further classes and methods
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| 62 | }
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| 63 | }
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| 64 |
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