This paper explores the computational challenge of incorporating equity in p-median facility
location models under uncertain demand and discusses how two-stage robust programming …

Bilevel optimization deals with nested problems in which a leader takes the first decision to
minimize their objective function while accounting for a follower's best-response reaction …

Mixed-integer non-linear programs (MINLPs) arise in various domains, such as energy
systems and transportation, but are notoriously difficult to solve. Recent advances in …

Besides training, mathematical optimization is also used in deep learning to model and
solve formulations over trained neural networks for purposes such as verification …

Adaptive robust optimization problems have received significant attention in recent years,
but remain notoriously difficult to solve when recourse decisions are discrete in nature. In …

In the realm of robust optimization the $ k $-adaptability approach is one promising method
to derive approximate solutions for two-stage robust optimization problems. Instead of …

We study the value function of an integer program (IP), which characterizes how the optimal
objective value changes as the right-hand sides vary. We show that the IP value function can …

We consider the robust routing problem with uncertain travel times under the min-max regret
criterion, which represents an extended and robust version of the classic traveling salesman …