Genetic Algorithm in Matlab
4 views (last 30 days)
Show older comments
Genetic Algorithm in Matlab : Basic Implementation .
%%steps
%1.Initialize the populations
tic
clc; clear all; close all;
par_size=6;
%Encode
for i=1:par_size
par(i,:)=dec2bin(round(1+1023*rand),10);
a(i) = bin2dec(par(i,:));
end
for iter = 1:100
%2.Evaluate fitness
fitness = zeros(1,par_size);
%The fitness function
%count the no of one's in the string
fitness = [sum(par=='1',2)].';
sum_fitness = sum(fitness)
prob_fitness = fitness./sum_fitness;
[~,I]=sort(prob_fitness);
%I is the order of the fitness value
prob_fitness_sort = prob_fitness(I);
%sorting
par = par(I,:);
%3.Select Parents
%Roulette wheel selection
%generate cumulative probability
cum_prob = zeros(size(prob_fitness));
A = zeros(size(prob_fitness));
for i=1:par_size
A(i) = prob_fitness_sort(i);
cum_prob(i) = sum(A);
end
new_pop = par;
%Selection being done
r1 = zeros(1,par_size);
for i=1:par_size
r1(i) = rand;
if r1(i)<=cum_prob(1)
new_pop(i,:) = par(1,:);
elseif r1(i)>cum_prob(1) && r1(i)<=cum_prob(2)
new_pop(i,:) = par(2,:);
elseif r1(i)>cum_prob(2) && r1(i)<=cum_prob(3)
new_pop(i,:) = par(3,:);
elseif r1(i)>cum_prob(3) && r1(i)<=cum_prob(4)
new_pop(i,:) = par(4,:);
elseif r1(i)>cum_prob(4) && r1(i)<=cum_prob(5)
new_pop(i,:) = par(5,:);
elseif r1(i)>cum_prob(5) && r1(i)<=cum_prob(6)
new_pop(i,:) = par(6,:);
end
end
%new_pop is the new particle sample
%4.Crossover and Mutate
%crossover
pc = 0.6; %pc is the crossover probability
for i=1:2:par_size %selecting adjacent couples
r2 = rand;
if r2<=pc
l = size(new_pop, 2);
%choose the parents
%here adjacent parents are taken
breeders(1,:)=new_pop(i,:);
breeders(2,:)=new_pop(i+1,:);
%choose a crossover point
cp = randperm(l, 1);
[i,cp];
%do crossover
b1 = [breeders(1, 1:cp), breeders(2, cp+1:end)];
b2 = [breeders(2, 1:cp), breeders(1, cp+1:end)];
new_pop(i,:) = b1;
new_pop(i+1,:) = b2;
end
end
%mutation
%pm be mutation probability
pm = 0.1;
for i=1:par_size
r2 = rand;
if r2<=pm %mutation probability is 0.1
%Do mutation
%select random position
r3 = 1+round((10-1)*rand);
[i,r3];
new_pop(i,r3)=num2str(abs(str2num(new_pop(i,r3))-1));
end
end
par = new_pop;
end
Is it correct ? Can it be improved ??
0 Comments
Answers (0)
See Also
Categories
Find more on Genetic Algorithm in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!