Binary Chromosome Encoding in Genetic Algorithm in Matlab

Hello everyone!

In this post, I am going to talk about the binary chromosome encoding in Genetic Algorithm in Matlab. More specifically, I will show you how to select the number of bits of the binary chromosome to correctly represent the solutions.

Here are the details of the optimization problem to be solved in this video.

Let’s see how it works . . .

……………………..

Matlab Code

population.m

function Y = population(n)
% n = population size
 
% It is noted that the number of bits to represent the variables 
% in binary numbers depends on the required accuracy (the number 
% of digits after comma)

Y=round(rand(n,33)); 

evaluation.m

function Y=evaluation(P)
[x1 y1]=size(P);
H=zeros(1,x1);
for i = 1:x1
    A=bi2de(P(i,1:18));
    x1=-3+A*(12.1-(-3))/(2^(18)-1);
    B=bi2de(P(i,18+1:y1));
    x2=4.1+B*(5.8-4.1)/(2^(15)-1);
    H(1,i)= 21.5 + x1*sin(4*pi*x1) + x2*sin(20*pi*x2);

end
Y=H; 

GA.m

clear all
close all
clc
%--------------------------------------------------------------------------
p=100; % Population size
c=50; % number of pairs of chromosomes to be crossovered
m=30; % number chromosomes to be mutated
tg=200; % Total number of generations 
%--------------------------------------------------------------------------
figure
title('Blue - Average         Red - Maximum');
xlabel('Generation')
ylabel('Objective Function Value')
hold on
P=population(p);
K=0;
[x1 y1]=size(P);
P1 = 0;
for i=1:tg   
    Cr=crossover(P,c);
    Mu=mutation(P,m);
    P(p+1:p+2*c,:)=Cr;
    P(p+2*c+1:p+2*c+m,:)=Mu;
.
.
.
Sorry! This is only a half of the Matlab code. 

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Thank you very much and good luck with your research and publications!