Hello all,
I have a problem with the runtime of my model. Namely, I found out that the step:
Pareto_X_TR(solu,p,s,m,i,j)$((solu.val = iter) AND f_c_r(s,m,i,j) AND p_s(p,s)) = x_TR.L(p,s,m,i,j);
takes a very long time. In this step I save the solution.
iter = 0;
Set
solu 'Number of possible solutions' / 1*%100000% /;
Parameter
Pareto_X_TR(solu,p,s,m,i,j) Results for variable x_TR
repeat
solve mod_epsmethod maximizing a_objval using minlp;
iter=iter+1;
Pareto_X_TR(solu,p,s,m,i,j)$((solu.val = iter) AND f_c_r(s,m,i,j) AND p_s(p,s)) = x_TR.L(p,s,m,i,j);
until (elapsed_time>time_limit);
The model should be solved thousands of times. The smaller the set solu is, the faster it goes.
Now my question: Is there a better approach for this that improves the performance significantly?
Many greetings
Janisch