Sample Average Approximation in AIMMS

Hi @mdlapitan. You have to add a set for the scenarios. Assume this set has an index 'sc’, and that you have a constraint like

Constraint c1 {
	IndexDomain: i;
	Definition: sum( j, q(i,j) * x(i,j) ) <= p(i);
}

Here p and q are parameters, and x is a variable. You then have to change this constraint into

Constraint c1 {
	IndexDomain: (sc,i);
	Definition: sum( j, q2(sc,i,j) * x(i,j) ) <= p2(sc,i);
}

So the parameters p and q get an extra index in their stochastic variant (p2 and q2). You then have to generate the data for p2 and q2, e.g., using distribution functions.

Note: it could be that you only need scenarios for q. In that case you only have to use q2 and do not need p2.