ga_f.m

遗传算法的实型表示实现

function result=GA_f(n,upbound,downbound,Pc,Pm)
% initilate the group
initial_gr=rand(100,n)*(upbound-downbound)+downbound;
%1000 generation
for j=1:1000
%perform selection
new_gr=selection_f(initial_gr,n,upbound,downbound);
%perform crossover
new_gr=crossover_f(new_gr,n,Pc);
%perform mutation
new_gr=mutation_f(new_gr,n,upbound,downbound,Pm);
initial_gr=new_gr;
if mod(j,100)==0
[tmp1,P]=evalF_f(new_gr,n,upbound,downbound);
tmp=min(tmp1)
end
end
[result,P]=evalF_f(new_gr,n,upbound,downbound);