萤火虫算法求解目标函数最小值，萤火虫算法求解目标函数极值，FA萤火虫算法寻优

clc clear close all r = 0.6;%光强吸收系数 a = 0.2;%扰动系数 d = 2;%变量个数 gen=100; %设置进化代数 popsize=200; %设置种群规模大小 pop = 10*rand(popsize,d)-5;%生成初始种群 xmax = [5 5];%变量上限 xmin = [-5 -5];%变量下限 fitness = fun(pop);%计算适应度 [best_fitness,mx] = max(fitness);%最佳适应度`q funtu(pop)%画图1 best_in_history = zeros(gen,1); %初始化全局历史最优解 best_in_history(1,1) = best_fitness; bestx = zeros(gen,d); bestx = pop(mx,:); for ij = 1:gen for ii = 1:popsize for jj = 1:popsize if fitness(ii)<fitness(jj)%比较荧光亮度 dij = fund(pop(ii,:),pop(jj,:));%计算距离 pop(ii,:) = pop(ii,:)+ fitness(jj)*exp(-r*dij^2)*(pop(jj,:)-pop(ii,:))+a*(0.2*rand(1,d)-0.1);%更新位置 end end end for ii = 1:popsize for jj = 1:d if pop(ii,jj)>xmax(jj) pop(ii,jj) = xmax(jj); elseif pop(ii,jj)<xmin(jj) pop(ii,jj) = xmin(jj); end end end fitness = fun(pop);%计算适应度 [best_fitness1,mx] = max(fitness);%最佳适应度 if best_fitness<best_fitness1 best_fitness = best_fitness1; bestx = pop(mx,:); end pop(mx,:) = pop(mx,:) + (rand(1,d)-0.5); best_in_history(ij,1) = best_fitness; end figure (2) plot(1./best_in_history,'k-') xlabel('迭代次数') ylabel('函数值') title('萤火虫求解函数极值收敛曲线') funtuz(bestx,pop)