We study a class of adversarial minimum-cost flow problems where the arcs are subject to
multiple ripple effect disruptions that increase their usage cost. The locations of the …

We propose a three-stage stochastic programming model to inform risk-averse investment in
power system resilience to winter storms. The first stage pertains to long-term investment in …

We study sequential shortest path interdiction, where in each period an interdictor with
incomplete knowledge of the arc costs blocks at most k arcs, and an evader with complete …

Many discrete optimization problems are amenable to constrained shortest-path
reformulations in an extended network space, a technique that has been key in …

We present a stochastic programming model for informing the deployment of ad hoc flood
mitigation measures to protect electric substations prior to an imminent and uncertain …

The ability of a system to tolerate disruptions and mitigate against malicious attacks is crucial
in many applications, especially when a failure of the system can have huge economic and …

Many relevant applications from diverse areas such as marketing, wildlife conservation, and
defending critical infrastructure can be modeled as interdiction games. In this work, we …

We consider the problem of learning classification trees that are robust to distribution shifts
between training and testing/deployment data. This problem arises frequently in high stakes …

In this paper, we study the mixed-integer nonlinear set given by a separable quadratic
constraint on continuous variables, where each continuous variable is controlled by an …

Catastrophic tornadoes cause severe damage and are a threat to human wellbeing, making
it critical to determine mitigation strategies to reduce their impact. One such strategy …