Ejemplo n.º 1
0
        static void Main(string[] args)
        {
            GA Ga;

            TravellingSalesman1dObjective Objective;
            TravelingSalesman2dObjective Objective2;

            int[] cities = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1400, 15000};
            Objective = new TravellingSalesman1dObjective(cities);

        
            //
            // Create the objective.
            //
            System.Collections.ArrayList cities2 = new System.Collections.ArrayList();
            //System.IO.StreamReader sr = System.IO.File.OpenText("../../xpf131.tsp");
            System.IO.StreamReader sr = System.IO.File.OpenText("../../xit1083.tsp");
            string s;
            bool gotime = false;
            s = sr.ReadLine();
            while ( s != null )
            {
                s.Trim();

                if ( !gotime )
                {
                    if (s == "NODE_COORD_SECTION" )
                    {
                        gotime = true;
                    }
                    s = sr.ReadLine();
                    continue;
                }
                if ( s == "EOF" )
                {
                    break;
                }
                
                string[] sa = s.Split(' ', '\t');
                if ( sa.Length != 3 )
                {
                    throw new Exception();
                }
                int city = Int32.Parse(sa[0]);
                int x = Int32.Parse(sa[1]);
                int y = Int32.Parse(sa[2]);

                cities2.Add( new Point(x, y) );
                s = sr.ReadLine();
            }
            sr.Close();

            //Point[] cities2 = new Point[] { };
            Objective2 = new TravelingSalesman2dObjective( (Point[]) cities2.ToArray(typeof(Point)));        


            //
            // Create the mutator
            //
            

            Ga = new GA();
            Ga.GeneDescriptors = new GeneDescriptor[] { new IntegerGeneDescriptor() };
            Ga.Homogeneous = true;
            //Ga.ChromosomeLength = cities.Length;
            Ga.ChromosomeLength = cities2.Count;

            Ga.Recombinator = new RecombinationDelegate( new genX.Recombination.PartiallyMatchedCrossover().Recombine );
            Ga.OrderMutator = new OrderMutationDelegate( genX.Reordering.Swap.Reorder );
            Ga.ValueMutator = null;
            Ga.Scaler = new ScalingDelegate( new genX.Scaling.LinearRankedFitnessScaler(1.6).Scale );
            Ga.RecombinationProbability = 0.7;

            Ga.PopulationSize       = 500;
//            Ga.Objective            = new ObjectiveDelegate( Objective.GetObjective );
            Ga.Objective            = new ObjectiveDelegate( Objective2.GetObjective );
            Ga.ObjectiveType        = ObjectiveType.MinimizeObjective;
            Ga.MaxGenerations       = 1000000;

            Ga.NewPopulation += new NewPopulationEventHandler( OnNewPopulation );

            Ga.Run();

            Console.WriteLine("Best Individual:");
            Console.WriteLine( Ga.Population.Summary.BestChromosome );
            Console.WriteLine("Finished.  Hit return.");
            Console.ReadLine();
        }
Ejemplo n.º 2
0
        static void Main(string[] args)
        {
            GA Ga;

            TravellingSalesman1dObjective Objective;
            TravelingSalesman2dObjective  Objective2;

            int[] cities = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1400, 15000 };
            Objective = new TravellingSalesman1dObjective(cities);


            //
            // Create the objective.
            //
            System.Collections.ArrayList cities2 = new System.Collections.ArrayList();
            //System.IO.StreamReader sr = System.IO.File.OpenText("../../xpf131.tsp");
            System.IO.StreamReader sr = System.IO.File.OpenText("../../xit1083.tsp");
            string s;
            bool   gotime = false;

            s = sr.ReadLine();
            while (s != null)
            {
                s.Trim();

                if (!gotime)
                {
                    if (s == "NODE_COORD_SECTION")
                    {
                        gotime = true;
                    }
                    s = sr.ReadLine();
                    continue;
                }
                if (s == "EOF")
                {
                    break;
                }

                string[] sa = s.Split(' ', '\t');
                if (sa.Length != 3)
                {
                    throw new Exception();
                }
                int city = Int32.Parse(sa[0]);
                int x    = Int32.Parse(sa[1]);
                int y    = Int32.Parse(sa[2]);

                cities2.Add(new Point(x, y));
                s = sr.ReadLine();
            }
            sr.Close();

            //Point[] cities2 = new Point[] { };
            Objective2 = new TravelingSalesman2dObjective((Point[])cities2.ToArray(typeof(Point)));


            //
            // Create the mutator
            //


            Ga = new GA();
            Ga.GeneDescriptors = new GeneDescriptor[] { new IntegerGeneDescriptor() };
            Ga.Homogeneous     = true;
            //Ga.ChromosomeLength = cities.Length;
            Ga.ChromosomeLength = cities2.Count;

            Ga.Recombinator             = new RecombinationDelegate(new genX.Recombination.PartiallyMatchedCrossover().Recombine);
            Ga.OrderMutator             = new OrderMutationDelegate(genX.Reordering.Swap.Reorder);
            Ga.ValueMutator             = null;
            Ga.Scaler                   = new ScalingDelegate(new genX.Scaling.LinearRankedFitnessScaler(1.6).Scale);
            Ga.RecombinationProbability = 0.7;

            Ga.PopulationSize = 500;
//            Ga.Objective            = new ObjectiveDelegate( Objective.GetObjective );
            Ga.Objective      = new ObjectiveDelegate(Objective2.GetObjective);
            Ga.ObjectiveType  = ObjectiveType.MinimizeObjective;
            Ga.MaxGenerations = 1000000;

            Ga.NewPopulation += new NewPopulationEventHandler(OnNewPopulation);

            Ga.Run();

            Console.WriteLine("Best Individual:");
            Console.WriteLine(Ga.Population.Summary.BestChromosome);
            Console.WriteLine("Finished.  Hit return.");
            Console.ReadLine();
        }