How to model multiple constraints using mixed integer linear programming?

For example,

I have 3 generators that must meet an hourly demand, but each of the generators has their own constraints.

Minimize: 15X1+25X2 (cost)

Subject to: X1+X2=250 (have to meet load), 0<=X1<=250 (min/max capacity for X1), 0<=X2<=150 (min/max capacity for X2)

Solving this example is easy, but if I wanted to add more constraints on X1 and X2 how would I go about this? Other constraints I would like to model are generator ramp rates and minimum up and down times. X1(i)+X1(i+1)<=ramp rate, X1ON(i)>=minimum up time

Thank you in advance for the help.

[Matt J]

You need to elaborate on the difficulty you're having. The additional constraints you've shown are still linear. Why is it harder to write the matrices A,b,Aeq,beq than you already did in the original version?

Answer 1

[Matt J]

As I commented above, I'm not completely clear on the difficulty being addressed here, but to create matrices A,b representing constraints X(i)+X(i+1)<=b(i), you could do as follows:

e=1:length(X)-1;
A=sparse([e;e],[e;e+1],1);
b=...