SA.zip_SA_局部搜索

clc,clear,close all warning off format longG % SA 参数 maxiter =1000; % 迭代次数 sizepop = 1000; % 种群数量 popmin = -50; popmax = 50; % x1 % popmin2 = -10; popmax2 = 10; % x2 T0 =8000; % initiation temperature q = 0.9; % 降温ratio Tend=10.^(-10); % 终止问题 % L = 100; % 链长 % 初始化种群 for i=1:sizepop pop(i,:) = popmin + (popmax-popmin)*rand(1,3); fitness(i) = fun( pop(i,:)); end % 记录一组最优值 [bestfitness,bestindex]=min(fitness); zbest=pop(bestindex,:); % 全局最佳 fitnesszbest=bestfitness; % 全局最佳适应度值 count = 1; % 迭代寻优 % while T0>Tend % 等价于迭代次数% maxiter = 200; % 迭代次数 for i=1: maxiter for j=1:sizepop % 产生新解 S1 = popmin + (popmax-popmin)*rand(1,3); % Metropolis法则判断是否接受新解 [S,fitness3] = Metropolis(S1,pop(j,:),T0); pop(j,:) = S; % 适应度更新 fitness(j) = fitness3; % 比较 个体间比较 if fitness(j)<bestfitness bestfitness = fitness(j); zbest = pop(j,:); end end % T0 = q*T0; % 更新当前温度 fitness_iter(i) = bestfitness; % fitness_iter(count) = bestfitness; % count = count+1; end disp('最优解') disp(zbest) fprintf('\n') bestfitness figure('color',[1,1,1]) % loglog(fitness_iter,'ro-','linewidth',2) plot(fitness_iter,'b','linewidth',2) grid on axis tight