C#实现粒子群优化算法(PSO)的例子（二元函数）

using System;

namespace PSO
{
    class Program
    {
        /* 已知函数 =(1,2)=1²+2² ，其中−10≤1,2≤10
        请用粒子群优化算法求解y的最小值 */

       static int N =100;//初始化种群大小
        int min = -10;
        int max = 10;//函数自变量取值范围
        double v_max = 5;
        double v_min = -5;//速度范围
        double w = 0.5;//惯量权重
        double c1 = 2;
        double c2 = 2;//加速系数
        Random r = new Random();//随机数
        double[,] particle = new double[N,2];//初始化3个粒子
        double[,] current_v = new double[N,2];//粒子当前速度
        double[,] pBest = new double[N, 2];//局部最优解
        double[] gBest = new double[2];//全局最优解
        double[] current_Fitness = new double[N];//粒子当前适应度（函数值）
        double[] particle_local_best_Fitness = new double[N];//粒子局部最优适应度（函数值）
        double particle_global_Fitness;//粒子全局最优适应度（函数值）
        public void Initial()//粒子初始化
        {
            int i, j;
            for (i = 0; i < N; i++)
            {
                for (j = 0; j < 2; j++)
                {
                    particle[i, j] = -min + (max - min) * r.NextDouble();//初始化群体
                    pBest[i, j] = particle[i, j];//将当前最优结果写入局部最优
                    current_v[i, j] = v_min + 2 * v_max * r.NextDouble(); //初始化粒子的速度
                }

            }

            for (i = 0; i < N; i++) //计算每个粒子的适应度
            {
                current_Fitness[i] = Fitness(particle[i, 0], particle[i, 1]);
                particle_local_best_Fitness[i] = current_Fitness[i];
            }

            particle_global_Fitness = particle_local_best_Fitness[0];//找出全局最优的适应度(函数值)
            j = 0;
            for (i = 0; i < N; i++)
            {
                if (particle_local_best_Fitness[i] < particle_global_Fitness)
                {
                    particle_global_Fitness = particle_local_best_Fitness[i];
                    j = i;
                }
            }

            for (i = 0; i < 2; i++) //更新全局最优向量
            {
                gBest[i] = pBest[j, i];
            }
            Console.WriteLine("初始化粒子完成!");
            Console.WriteLine("正在进行迭代...");
        }

        public void Renew_location()//迭代更新粒子所在的位置和速度
        {
            for (int i = 0; i < N; i++)
            {
                for (int j = 0; j < 2; j++)
                {
                    double r1 = r.NextDouble();
                    double r2 = r.NextDouble();
                    current_v[i, j] += (w * current_v[i, j] + c1 * r1 * (pBest[i, j] - particle[i, j]) +
                        c2 * r2 * (gBest[j] - particle[i, j]));//更新速度
                    particle[i, j] += current_v[i, j];//更新位置
                    if (particle[i, j] > max)//越界的位置，合法性调整(定义域范围内)
                    {
                        particle[i, j] = max;
                    }
                    if (particle[i, j] < min)
                    {
                        particle[i, j] = min;
                    }
                }
            }

        }
        static double Fitness(double x1, double x2)            //返回y=f(x1,x2)=x1²+x2²的函数值
        {
            return Math.Pow(x1, 2.0) + Math.Pow(x2, 2.0);
        }

       
        public void Renew_Fitness()//评估例子的适应度函数值
        {
            int j = -1;
            for (int i = 0; i < N; i++)
            {
                if (Fitness(particle[i, 0], particle[0, 1]) < current_Fitness[i])//更新局部最优解pBest
                {
                    pBest[i, 0] = particle[i, 0];
                    pBest[i, 1] = particle[i, 1];
                }
                particle_local_best_Fitness[i] = Fitness(pBest[i, 0], pBest[i, 1]);//更新局部最优适应值

                if (particle_local_best_Fitness[i] < particle_global_Fitness)//更新全局最优适应度
                {
                    particle_global_Fitness = particle_local_best_Fitness[i];
                    j = i;
                }
            }
          

        }
        static void Main(string[] args)
        {
            Program PSO = new Program();
            PSO.Initial();
            for (int i = 0; i < 10000; i++)//迭代10000次
            {
                PSO.Renew_location();
                PSO.Renew_Fitness();
            }
            Console.WriteLine("迭代完成，最小值y={0}", PSO.particle_global_Fitness);
            Console.ReadLine();
        }
    }
}