Changeset 17559 for branches/2825-NSGA3/HeuristicLab.Algorithms.NSGA3/3.3/NSGA3.cs

Timestamp:

05/25/20 19:33:28 (4 years ago)

Author:

dleko

Message:

#2825: Initialize and analyze solutions of first generation.

File:

• branches/2825-NSGA3/HeuristicLab.Algorithms.NSGA3/3.3/NSGA3.cs (modified) (6 diffs)

branches/2825-NSGA3/HeuristicLab.Algorithms.NSGA3/3.3/NSGA3.cs

@@ -10 +10 @@
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
+using HeuristicLab.Random;
 
 namespace HeuristicLab.Algorithms.NSGA3
@@ -66 +67 @@
 
         private const string GeneratedReferencePointsResultName = "Generated Reference Points";
+        private const string CurrentFrontResultName = "Pareto Front"; // Do not touch this
 
         #endregion ParameterAndResultsNames
@@ -132 +134 @@
             get { return (DoubleMatrix)Results[GeneratedReferencePointsResultName].Value; }
             set { Results[GeneratedReferencePointsResultName].Value = value; }
+        }
+
+        public DoubleMatrix ResultsSolutions
+        {
+            get { return (DoubleMatrix)Results[CurrentFrontResultName].Value; }
+            set { Results[CurrentFrontResultName].Value = value; }
         }
 
@@ -173 +181 @@
             base.Initialize(cancellationToken);
 
+            InitFields();
             InitResults();
             InitReferencePoints();
+            Analyze();
         }
 
@@ -186 +196 @@
         #region Private Methods
 
+        private void InitFields()
+        {
+            random = new MersenneTwister();
+            InitSolutions();
+        }
+
         private void InitResults()
         {
             Results.Add(new Result(GeneratedReferencePointsResultName, "The initially generated reference points", new DoubleMatrix()));
-        }
-
-        // Generates the structured reference points
+            Results.Add(new Result(CurrentFrontResultName, "The Pareto Front", new DoubleMatrix()));
+        }
+
         private void InitReferencePoints()
         {
@@ -200 +216 @@
         }
 
+        private void InitSolutions()
+        {
+            int minBound = 0; // todo: find min inside Problem.Encoding
+            int maxBound = 1; // todo: find max inside Problem.Encoding
+
+            // Initialise solutions
+            solutions = new Solution[PopulationSize.Value];
+            for (int i = 0; i < PopulationSize.Value; i++)
+            {
+                RealVector randomRealVector = new RealVector(Problem.Encoding.Length, random, minBound, maxBound);
+
+                solutions[i] = new Solution(StorableConstructorFlag.Default)
+                {
+                    Chromosome = randomRealVector
+                };
+                solutions[i].Fitness = Evaluate(solutions[i].Chromosome);
+            }
+        }
+
+        /// <summary>
+        /// Returns the fitness of the given <paramref name="chromosome" /> by applying the Evaluate
+        /// method of the Problem.
+        /// </summary>
+        /// <param name="chromosome"></param>
+        /// <returns></returns>
+        private double[] Evaluate(RealVector chromosome)
+        {
+            return Problem.Evaluate(new SingleEncodingIndividual(Problem.Encoding, new Scope { Variables = { new Variable(Problem.Encoding.Name, chromosome) } }), random);
+        }
+
+        private void Analyze()
+        {
+            ResultsSolutions = solutions.Select(s => s.Chromosome.ToArray()).ToMatrix();
+            Problem.Analyze(
+                solutions.Select(s => (Individual)new SingleEncodingIndividual(Problem.Encoding, new Scope { Variables = { new Variable(Problem.Encoding.Name, s.Chromosome) } })).ToArray(),
+                solutions.Select(s => s.Fitness).ToArray(),
+                Results,
+                random
+                );
+        }
+
         #endregion Private Methods
     }