matlab 量子粒子群算法+levy飞行的改进 可执行算法

clc,clear,close all warning off format longG % 量子粒子群算法 % PSO 参数 c1 = 1.4995; c2 = 1.4995; Vmin = -1; Vmax = 1; maxgen = 200; % 迭代次数 sizepop = 20; % 种群数量 popmin1 = -1; popmax1 = 1; % x1 popmin2 = -1; popmax2 = 1; % x2 beta = 1.5; % beta控制常数 nvar = 2; % 2个未知量 % 初始化种群 for i=1:sizepop x1 = popmin1 + (popmax1-popmin1)*rand; x2 = popmin2 + (popmax2-popmin2)*rand; pop(i,1) = x1; pop(i,2) = x2; fitness(i) = fun([x1,x2]); V(i,1) = 0; V(i,2) = 0; end % 记录一组最优值 [bestfitness,bestindex]=min(fitness); zbest=pop(bestindex,:); % 全局最佳 gbest=pop; % 个体最佳 fitnessgbest=fitness; % 个体最佳适应度值 fitnesszbest=bestfitness; % 全局最佳适应度值 % 迭代寻优 for iter=1:maxgen for j=1:sizepop mbest = mean(gbest); % 速度更新 r1 = rand; r2 = rand; V(j,:) = ( c1*r1*( gbest(j,:) ) + c2*r2*( zbest ) ) / ( c1*r1+c2*r2 ); % V--x1 if V(j,1)>Vmax V(j,1)=Vmax; end if V(j,1)<Vmin V(j,1)=Vmin; end % V--x2 if V(j,2)>Vmax V(j,2)=Vmax; end if V(j,2)<Vmin V(j,2)=Vmin; end % 个体更新 u = rand; if u>0.5 pop(j,:) = Levy(beta,nvar).*(pop(j,:)-zbest) + ( 0.5+0.5*(maxgen-iter)/maxgen ).*abs(mbest-pop(j,:)) .*log(u); % pop(j,:) = Levy(beta,nvar) + ( 0.5+0.5*(maxgen-iter)/maxgen ).*abs(mbest-pop(j,:)) .*log(u); else pop(j,:) = Levy(beta,nvar).*(pop(j,:)-zbest) - ( 0.5+0.5*(maxgen-iter)/maxgen ).*abs(mbest-pop(j,:)) .*log(u); % pop(j,:) = Levy(beta,nvar) - ( 0.5+0.5*(maxgen-iter)/maxgen ).*abs(mbest-pop(j,:)) .*log(u); end % x1 if pop(j,1)>popmax1 pop(j,1)=popmax1; end if pop(j,1)<popmin1 pop(j,1)=popmin1; end % x2 if pop(j,2)>popmax2 pop(j,2)=popmax2; end if pop(j,2)<popmin2 pop(j,2)=popmin2; end % 适应度更新 fitness(j) = fun(pop(j,:)); % 比较 个体间比较 if fitness(j)<fitnessgbest(j) fitnessgbest(j) = fitness(j); gbest(j,:) = pop(j,:); end if fitness(j)<bestfitness bestfitness = fitness(j); zbest = pop(j,:); end end fitness_iter(iter) = bestfitness; end disp('最优解') disp(zbest) fprintf('\n') figure('color',[1,1,1]) % plot(fitness_iter,'ro-','linewidth',2) loglog(fitness_iter,'ro-','linewidth',2) axis tight grid on