Finding feasible solution with intlinprog
8 views (last 30 days)
Show older comments
I'm using intlinprog to solve some bigger MILP problems (hundreds or few thousands of variables and constraints).
The solver typically finds solutions after seconds or few minutes. So far so good.
Sometimes I'm interested in just quickly finding a feasible solution for the constraints.
To do this I set the vector for the objective function to the zero vector. When I now start
the optimization it runs and runs and runs (hours...) .... until the timeLimit is reached.
My questions:
a) How can that be? The second optimization is much simpler than the first (the optimal value is
even known: 0) but it does not converge.
b) If this does not work, what could be an alternative way to (quickly) find a feasible solution?
Thanks,
Steffen.
0 Comments
Answers (1)
Alan Weiss
on 9 Jul 2020
A nonzero objective function vector can sometimes help intlinprog by breaking symmetry in the constraints. It is never clear with integer linear programming whether specific changes will speed a solution. For more information, see Tuning Integer Linear Programming.
You are free to specify f = [], which probably works the same as specifying an all-zero vector. See f.
Alan Weiss
MATLAB mathematical toolbox documentation
See Also
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!