December 06, 2022
Prof. Enrico Malaguti from University of Bologna
will give a presentation on
"Chance-constrained problems with integer second-stage recourse decisions”
We study a class of chance-constrained two-stage stochastic optimization problems where the second-stage recourse decisions belong to mixed-integer convex sets.
Due to the nonconvexity of the second-stage feasible sets, standard decomposition approaches cannot be applied. We develop a provably convergent branch-and-cut scheme that
iteratively generates valid inequalities for the convex hull of the second-stage feasible sets, resorting to spatial branching when cutting no longer suffices. We show that this algorithm
attains an approximate notion of convergence, whereby the feasible sets are relaxed by some positive tolerance. Computational results on chance-constrained resource planning problems
indicate that our implementation of the proposed algorithm is highly effective in solving this class of problems, compared to a naive reformulation tackled with a state-of-the-art MIP solver.
For logistic reasons, please note that the seminar will hold at 14h instead of the usual 16h.