PSO.rar_PSO_deep42g_swarm_算例_粒子群

% Initialization %初始化 clear clc n = 50; % "鸟群大小 bird_setp = 50; % 最大迭代次数 dim = 3; % 维度 c2 =1.2; % 加速因子，为正 c1 = 0.12; % 加速因子 w =0.9; % 惯性因子 fitness=zeros(n,bird_setp); %目标函数 R1 = rand(dim,n); %[0,1]的随机数组 R2 = rand(dim,n); %随机数 current_fitness =zeros(n,1); %局部最优 %-------------------------% % 初始化种群、速度和位置 %--------------------------% current_position = 10*(rand(dim, n)-.5); velocity = .3*randn(dim, n) ; pbest = current_position ; %-----------------------% % 评价初始种群 % %--------------------- -% for i = 1:n current_fitness(i) = fs(current_position(:,i),dim); % 计算目标函数 end local_best_fitness = current_fitness ; %局部最优目标值 [global_best_fitness,g] = min(local_best_fitness) ; %全局最优目标值 for i=1:n gbest(:,i) = pbest(:,g) ; % 全局最优位置和局部最优位置的关系 end velocity = w *velocity + c1*(R1.*(pbest-current_position)) + c2*(R2.*(gbest-current_position)); % 速度的变化公式 current_position = current_position + velocity ; %位置的变化公式 %% Main Loop iter = 0 ; % Iterations counter 迭代次数的计算统计 while ( iter < bird_setp ) iter = iter + 1; for i = 1:n, current_fitness(i) = fs(current_position(:,i),dim) ; %利用Live_fn函数求当前最优目标值 end for i = 1 : n if current_fitness(i) < local_best_fitness(i) %若当前局部最优目标值小于上一次的目标值 local_best_fitness(i) = current_fitness(i); %局部最优值改变为当前值 pbest(:,i) = current_position(:,i) ; %局部最优位置改变为当前位置 end end [current_global_best_fitness,g] = min(local_best_fitness); %全局最优目标值等于局部最优目标值中的最小值 if current_global_best_fitness < global_best_fitness %将当前全局最优目标值与上一次目标值进行比较 global_best_fitness = current_global_best_fitness; %全局最优目标值等于当前的目标值 for i=1:n gbest(:,i) = pbest(:,g); %全局最优位置改变 end end velocity = w *velocity + c1*(R1.*(pbest-current_position)) + c2*(R2.*(gbest-current_position)); current_position = current_position + velocity; x=current_position(1,:); %最优位置的横坐标 y=current_position(2,:); %最优位置的纵坐标 z=current_position(3,:); %clf %清除上一次图形 % plot(x,y,'h') % hold on % plot(x, y,'r:'); %将(x,y)的散点图画出 plot3(x,y,z,'h') % hold on % plot3(x,y,z,'m:') axis([-5 5 -5 5 -5 5]); pause(.2) %暂停程序执行，进入下一次迭代 end [Jbest_min,I] = min(current_fitness) %全局最优目标值，及下标 X=current_position(:,I) %全局最优位置 %