Week 4.1 - Genetic Algorithm
close all
clear all
clc
%input
x = linspace(0,0.6,150);
y = linspace(0,0.6,150);
num_spaces = 50;
%forming 2d array
[xx,yy] =meshgrid(x,y);
for i=1:length(x)
for j=1:length(y)
input_vector(1)= xx(i,j);
input_vector(2)= yy(i,j);
f(i,j) = stalagmite(input_vector);
end
end
%study 1-unbounded
tic
for i=1:num_spaces
[results,fopt(i)] = ga(@stagalmite,2)
xopt(i)=results(1)
yopt(i)=results(2)
end
study_time1=toc
figure(1)
subplot(2,1,1)
surf(x,y,-f)
shading interp
hold on
plot3(xopt,yopt,-fopt,'marker','0')
subplot(2,1,2)
plot(-fopt)
xlabel('iteration')
ylabel('function maximum')
%study 2-bounded
tic
for i=1:num_spaces
[results,fopt(i)] = ga(@stagalmite,2,[],[],[],[],[0;0],[0.6;0.6])
xopt(i) = results(1)
yopt(i) = results(2)
end
study_time2=toc
figure(2)
subplot(2,1,1)
surf(x,y,-f)
shading interp
hold on
plot3(xopt,yopt,-fopt,'marker','o')
subplot(2,1,2)
plot(-fopt)
xlabel('iteration')
ylabel('function maximum')
%study3 - increased initial population
tic
options= optimoptions ('ga')
options= optimoptions(options,'populationsize',250)
for i = 1:num_spaces
[results,fopt(i)] = ga(@stagalmite, 2, [],[],[],[],[0;0],[0.6;0.6],[],[],options)
xopt(i) = results(1)
yopt(i) = results(2)
end
study_time3=toc
figure(3)
subplot(2,1,1)
surf(x,y,-f)
shading interp
hold on
plot3(xopt,yopt,-fopt,'marker','o')
subplot(2,1,2)
plot(-fopt)
xlabel('iteration')
ylabel('function maximum')
stalagmite function code:-
function A = stagalmite (input_vector)
x= input_vector(1);
y=imput_vector(2);
f1=(sin(5.1*pi*x+0.5)).^6;
f2=exp((-4*log(2)*((x-0.0667).^2))/0.64);
f3=(sin(5.1*pi*y+0.5)).^6;
f4=exp((-4*log(2)*((y-0.0667).^2))/0.64);
A = -(f1*f2*f3*f4);
end