Ejemplo n.º 1
0
        public static double Solve(int population_size, int dimension_count, CostEvaluationMethod evaluator, CreateBeeMethod generator, out Bee global_best_solution, double[] lower_bounds = null, double[] upper_bounds = null, object constraints = null, double tolerance = 0.000001, int maxIterations = 100000)
        {
            BeeSwarm <Bee> solver = new BeeSwarm <Bee>(60, 15, 30, 20, 10, evaluator, generator);

            solver.LowerBounds       = lower_bounds;
            solver.UpperBounds       = upper_bounds;
            solver.Constraints       = constraints;
            solver.LocalSearchRegion = new double[dimension_count];
            for (int i = 0; i < dimension_count; ++i)
            {
                solver.LocalSearchRegion[i] = (upper_bounds[i] - lower_bounds[i]) / 1000;
            }

            solver.Initialize();
            int    iteration                      = 0;
            double cost_reduction                 = tolerance;
            double global_best_solution_cost      = solver.GlobalBestSolutionCost;
            double prev_global_best_solution_cost = global_best_solution_cost;

            while (cost_reduction >= tolerance && iteration < maxIterations)
            {
                prev_global_best_solution_cost = global_best_solution_cost;
                solver.Iterate();
                global_best_solution_cost = solver.GlobalBestSolutionCost;
                cost_reduction            = prev_global_best_solution_cost - global_best_solution_cost;
                iteration++;
            }

            global_best_solution = solver.GlobalBestSolution.Clone() as Bee;

            return(global_best_solution_cost);
        }
Ejemplo n.º 2
0
        public static double Solve(int dimension_count, CostEvaluationMethod evaluator, out Bee global_best_solution, double[] lower_bounds = null, double[] upper_bounds = null, int maxIterations = 100000, int displayEvery = 100, object constraints = null)
        {
            int            scoutBeeCount = 60;
            int            bestPatch     = 15;
            int            elitePatch    = 30;
            BeeSwarm <Bee> solver        = new BeeSwarm <Bee>(scoutBeeCount, bestPatch, elitePatch, 20, 10, evaluator);

            solver.LowerBounds       = lower_bounds;
            solver.UpperBounds       = upper_bounds;
            solver.Constraints       = constraints;
            solver.LocalSearchRegion = new double[dimension_count];
            for (int i = 0; i < dimension_count; ++i)
            {
                solver.LocalSearchRegion[i] = (upper_bounds[i] - lower_bounds[i]) / bestPatch;
            }

            solver.Initialize();
            int    iteration = 0;
            double global_best_solution_cost      = solver.GlobalBestSolutionCost;
            double prev_global_best_solution_cost = global_best_solution_cost;

            while (iteration < maxIterations)
            {
                prev_global_best_solution_cost = global_best_solution_cost;
                solver.Iterate();
                global_best_solution_cost = solver.GlobalBestSolutionCost;
                if (iteration % displayEvery == 0)
                {
                    Console.WriteLine("Generation: {0}, Best Cost: {1}", iteration, global_best_solution_cost);
                }
                iteration++;
            }

            global_best_solution = solver.GlobalBestSolution.Clone() as Bee;

            return(global_best_solution_cost);
        }