/// <summary>
        /// Usage:
        ///     - NSGAIImTSP
        /// </summary>
        /// <param name="args">Command line arguments.</param>
        public static void Main(string[] args)
        {
            Problem   problem;                      // The problem to solve
            Algorithm algorithm;                    // The algorithm to use
            Operator  crossover;                    // Crossover operator
            Operator  mutation;                     // Mutation operator
            Operator  selection;                    // Selection operator

            Dictionary <string, object> parameters; // Operator parameters

            QualityIndicator indicators;            // Object to get quality indicators

            // Logger object and file to store log messages
            var logger = Logger.Log;

            var appenders    = logger.Logger.Repository.GetAppenders();
            var fileAppender = appenders[0] as log4net.Appender.FileAppender;

            fileAppender.File = "NSGAIImTSP.log";
            fileAppender.ActivateOptions();

            indicators = null;
            problem    = new MTSP("Permutation", "kroA150.tsp", "kroB150.tsp");

            algorithm = new JMetalCSharp.Metaheuristics.NSGAII.NSGAII(problem);
            //algorithm = new ssNSGAII(problem);

            // Algorithm parameters
            algorithm.SetInputParameter("populationSize", 100);
            algorithm.SetInputParameter("maxEvaluations", 10000000);

            /* Crossver operator */
            parameters = new Dictionary <string, object>();
            parameters.Add("probability", 0.95);
            //crossover = CrossoverFactory.getCrossoverOperator("TwoPointsCrossover", parameters);
            crossover = CrossoverFactory.GetCrossoverOperator("PMXCrossover", parameters);

            /* Mutation operator */
            parameters = new Dictionary <string, object>();
            parameters.Add("probability", 0.2);
            mutation = MutationFactory.GetMutationOperator("SwapMutation", parameters);

            /* Selection Operator */
            parameters = null;
            selection  = SelectionFactory.GetSelectionOperator("BinaryTournament", parameters);

            // Add the operators to the algorithm
            algorithm.AddOperator("crossover", crossover);
            algorithm.AddOperator("mutation", mutation);
            algorithm.AddOperator("selection", selection);

            // Add the indicator object to the algorithm
            algorithm.SetInputParameter("indicators", indicators);

            // Execute the Algorithm
            long        initTime      = Environment.TickCount;
            SolutionSet population    = algorithm.Execute();
            long        estimatedTime = Environment.TickCount - initTime;

            // Result messages
            logger.Info("Total execution time: " + estimatedTime + "ms");
            logger.Info("Variables values have been writen to file VAR");
            population.PrintVariablesToFile("VAR");
            logger.Info("Objectives values have been writen to file FUN");
            population.PrintObjectivesToFile("FUN");

            if (indicators != null)
            {
                logger.Info("Quality indicators");
                logger.Info("Hypervolume: " + indicators.GetHypervolume(population));
                logger.Info("GD         : " + indicators.GetGD(population));
                logger.Info("IGD        : " + indicators.GetIGD(population));
                logger.Info("Spread     : " + indicators.GetSpread(population));
                logger.Info("Epsilon    : " + indicators.GetEpsilon(population));

                int evaluations = (int)algorithm.GetOutputParameter("evaluations");
                logger.Info("Speed      : " + evaluations + " evaluations");
            }
        }
Exemple #2
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        /// <summary>
        /// Usage: three options
        ///     - NSGAII
        ///     - NSGAII problemName
        ///     - NSGAII problemName paretoFrontFile
        /// </summary>
        /// <param name="args"></param>
        public static void Main(string[] args)
        {
            Problem   problem;                      // The problem to solve
            Algorithm algorithm;                    // The algorithm to use
            Operator  crossover;                    // Crossover operator
            Operator  mutation;                     // Mutation operator
            Operator  selection;                    // Selection operator

            Dictionary <string, object> parameters; // Operator parameters

            QualityIndicator indicators;            // Object to get quality indicators

            // Logger object and file to store log messages
            var logger = Logger.Log;

            var appenders    = logger.Logger.Repository.GetAppenders();
            var fileAppender = appenders[0] as log4net.Appender.FileAppender;

            fileAppender.File = "NSGAII.log";
            fileAppender.ActivateOptions();

            indicators = null;
            if (args.Length == 1)
            {
                object[] param = { "Int", RowCol[1], RowCol[0], Matrix };
                problem = ProblemFactory.GetProblem(args[0], param);
            }
            else if (args.Length == 2)
            {
                object[] param = { "Real" };
                problem    = ProblemFactory.GetProblem(args[0], param);
                indicators = new QualityIndicator(problem, args[1]);
            }
            else
            {             // Default problem
                //problem = new Kursawe("Real", 3);
                //problem = new Kursawe("BinaryReal", 3);
                //problem = new Water("Real");
                //problem = new ZDT3("ArrayReal", 30);
                //problem = new ConstrEx("Real");
                //problem = new DTLZ1("Real");
                //problem = new OKA2("Real") ;
                //problem = new JMetalCSharp.Problems.Fonseca.Fonseca("Real");
                problem = new JMetalCSharp.Problems.Regression.Regression("Int", RowCol[1], RowCol[0], Matrix);
                //problem = new JMetalCSharp.Problems.IntRealProblem.IntRealProblem("Int");
            }

            algorithm = new JMetalCSharp.Metaheuristics.NSGAII.NSGAII(problem);
            //algorithm = new ssNSGAII(problem);

            // Algorithm parameters
            algorithm.SetInputParameter("populationSize", 500);            //500
            algorithm.SetInputParameter("maxEvaluations", 25000);          //25000

            // Mutation and Crossover for Real codification
            parameters = new Dictionary <string, object>();
            parameters.Add("probability", 0.9);
            parameters.Add("distributionIndex", 20.0);
            crossover = CrossoverFactory.GetCrossoverOperator("SinglePointCrossover", parameters);

            parameters = new Dictionary <string, object>();
            parameters.Add("probability", 1.0 / problem.NumberOfVariables);
            parameters.Add("distributionIndex", 20.0);
            mutation = MutationFactory.GetMutationOperator("BitFlipMutation", parameters);

            // Selection Operator
            parameters = null;
            selection  = SelectionFactory.GetSelectionOperator("BinaryTournament2", parameters);

            // Add the operators to the algorithm
            algorithm.AddOperator("crossover", crossover);
            algorithm.AddOperator("mutation", mutation);
            algorithm.AddOperator("selection", selection);

            // Add the indicator object to the algorithm
            algorithm.SetInputParameter("indicators", indicators);

            // Execute the Algorithm
            long        initTime   = Environment.TickCount;
            SolutionSet population = algorithm.Execute();

            estimatedTime = Environment.TickCount - initTime;

            // Result messages
            logger.Info("Total execution time: " + estimatedTime + "ms");
            logger.Info("Variables values have been writen to file VAR");
            population.PrintVariablesToFile("VAR");
            logger.Info("Objectives values have been writen to file FUN");
            population.PrintObjectivesToFile("FUN");
            Console.WriteLine("Time: " + estimatedTime);
            Console.ReadLine();
            if (indicators != null)
            {
                logger.Info("Quality indicators");
                logger.Info("Hypervolume: " + indicators.GetHypervolume(population));
                logger.Info("GD         : " + indicators.GetGD(population));
                logger.Info("IGD        : " + indicators.GetIGD(population));
                logger.Info("Spread     : " + indicators.GetSpread(population));
                logger.Info("Epsilon    : " + indicators.GetEpsilon(population));

                int evaluations = (int)algorithm.GetOutputParameter("evaluations");
                logger.Info("Speed      : " + evaluations + " evaluations");
            }
        }