The ga-function (genetic algorithm) gives me totally random and wrong solutions?

Hello! I have a super easy puzzle that I would like to solve, and I have tried multiple solvers and found the ga to be the easiest to use, but it just gives me totally random and wrong results.

Here is my objective function/problem: min f = x(1)*x(3)+x(2)*x(4)*100;

lower and upper bounds för x_n are:

ub = [1 1 1 1];

lb = [0.4 0 0 0];

x(3) and x(4) have to be equal to 0 or 1, therefore intcon = [3 4];

my constraints are: x(1)*x(3)+x(2)*x(4)-load=0 where the load can vary between 0 and 2.

The problem is that the ga function just randomly give me different solutions which can be correct or wrong depending on how many times I hit "run". How can I overcome this problem? Or have anyone a better way to solve this problem?

Thank you very much!

Here is my code:

function ga_fraga

ub = [1 1 1 1];

lb = [0.4 0 0 0];

intcon = [3 4];

[xval fval]=ga(@myfun,length(lb),[],[],[],[],lb,ub,@nonlcon,intcon);

xval(1:2).*xval(3:4)

fval

end

function [c,ceq] = nonlcon(x)

load=0.6;

c = [];

ceq = [];

c(1) = x(1)*x(3)+x(2)*x(4)-load;

c(2) = -c(1);

end

function f = myfun(x)

f = x(1)*x(3)+x(2)*x(4)*100;

end

Answer 1

[Nayan Rawat]

Use fmincon