how can i solve this problem using genetic algorithm in matlab??

min z = dny1/24+ dpy2/0.6+dnx1/0.3+dpx1/0.3+dnx2/0.3+dpx2/0.3+dnx3/0.3+dpx3/0.3+dnx4/0.3+dpx4/0.3;

y1 = 27.3702+40.2381*x1-1.1667*x2-0.4685*x3+0.5000*x4; 
y2 = 2.5705+0.8908*x1-0.1067*x2+0.0306*x3+0.0359*x4;

y1+dny1 > = 68;
my1+dny1/4=1;
dny1 >=1; 

y2-dpy2 < = 3.3;
my2+dpy2/0.1=1;
dpy2 <=1; 

x1+dnx1 > = 0.6;
x1-dpx1 < = 1.2;
mx1+dpx1/0.05+dnx1/0.05 =1;
dpx1<=0.05;
dnx1<=0.05; 

x2+dnx2 > =4;
x2-dpx2 < =8;
mx2+dpx2/0.05+dnx2/0.05 =1;
dpx2<=0.05;
dnx2<=0.05;

x3+dnx3 > = 8;
x3-dpx3 < = 15;
mx3+dpx3/0.05+dnx3/0.05 =1;
dpx3<=0.05;
dnx3<=0.05;

x4+dnx4 > = 8;
x4-dpx4 < = 16;
mx4+dpx4/0.05+dnx4/0.05 =1;
dpx4<=50;
dnx4<=50;

Answer 1

[Walter Roberson]

Use ga() and code a bunch of upper bounds and lower bounds and linear inequalities .

What you wrote at first looks like there are also linear equalities such as

my1+dny1/4=1;

but in each case you do not otherwise use the m* variable, so those are meaningless constraints. Unless, that is, "my1" means something different than a variable named "my1" ?