How to avoid unnecessary optimvar variable declarations in Problem Based Optimization Models?

Hi, I have the following piece of code:

X = optimvar('X',{Nodes,Nodes,Trees},'LowerBound',0,'UpperBound',1,'Type','integer');
Y = optimvar('Y',{Nodes,Trees},'LowerBound',0,'UpperBound',1,'Type','integer');
for k = 1:K
    for i = 1:n
        X(i,i,k).UpperBound = 0;
        for j = i + 1:n
            X(j,i,k).UpperBound = 0;
        end
    end
end

I want the decision variable X(i,j,k) be created only for i < j for example. Or some parameter C(i,j) > 0. What is the best way to do that in order to avoid loops.

Best Regards Ramiro

[Matt J]

I would hope that you don't have to care. There's a chance that the problem-based optimization engine is smart enough to pre-detect extra variables for which LowerBound=UpperBound and do the appropriate problem simplification for you internally.

Answer 1

[Matt J]

Or some parameter C(i,j) > 0.

X = optimvar('X',[1,nnz(C>0)], 'LowerBound',0,'UpperBound',1,'Type','integer')

but you would have to reformulate the objective and other constraints to accomodate the linear indexing.