simplega.m

修改自wiley的书中的各种遗传算法（GA）matlab代码

% This is a simple GA written in MATLAB
% costfunction.m calculates a cost for each row or
% chromosome in pop. This function must be provided
% by the user.
N=200; % number of bits in a chromosome
M=8; % number of chromosomes must be even
last=50; % number of generations
sel=0.5; % selection rate
M2=2*ceil(sel*M/2); % number of chromosomes kept
mutrate=0.01; % mutation rate
nmuts=mutrate*N*(M-1); % number of mutations
% creates M random chromosomes with N bits
pop=round(rand(M,N)); % initial population
for ib=1:last
cost=costfunction(pop); % cost function
% ranks results and chromosomes
[cost,ind]=sort(cost);
pop=pop(ind(1:M2),:);
[ib cost(1)]
%mate
cross=ceil((N-1)*rand(M2,1));
% pairs chromosomes and performs crossover
for ic=1:2:M2
pop(ceil(M2*rand),1:cross)=pop(ic,1:cross);
pop(ceil(M2*rand),cross+1:N)=pop(ic+1,cross+1:N);
pop(ceil(M2*rand),1:cross)=pop(ic+1,1:cross);
pop(ceil(M2*rand),cross+1:N)=pop(ic,cross+1:N);
end
%mutate
for ic=1:nmuts
ix=ceil(M*rand);
iy=ceil(N*rand);
pop(ix,iy)=1-pop(ix,iy);
end %ic
end %ib