基本的遗传算法MATLAB实现

function main() clear; clc; popsize=100; chromlength=10; pc = 0.6; pm = 0.001; pop = initpop(popsize,chromlength); for i = 1:100 objvalue = cal_objvalue(pop); fitvalue = objvalue; newpop = selection(pop,fitvalue); newpop = crossover(newpop,pc); newpop = mutation(newpop,pm); pop = newpop; [bestindividual,bestfit] = best(pop,fitvalue); x2 = binary2decimal(bestindividual); x1 = binary2decimal(newpop); y1 = cal_objvalue(newpop); if mod(i,10) == 0 figure; fplot(@(x)10*sin(5*x)+7*abs(x-5)+10,[0 10]); hold on; plot(x1,y1,'*'); title(['迭代次数为n=' num2str(i)]); %plot(x1,y1,'*'); end end fprintf('The best X is --->>%5.4f\n',x2); fprintf('The best Y is --->>%5.2f\n',bestfit);