Uncertainties are the most significant challenges in the smart power system, necessitating
the use of precise techniques to deal with them properly. Such problems could be effectively …

Due to the global outbreak of COVID-19, the perishable product supply chains have been
impacted in different ways, and consequently, the risks of food insecurity have been …

This study provides a thorough analysis of unit commitment (UC) formulations in the context
of low-inertia power systems, which are increasingly prevalent as the transition to …

This paper studies distributionally robust chance constrained programs (DRCCPs), where
the uncertain constraints must be satisfied with at least a probability of a prespecified …

Chance-constrained programs (CCPs) constitute a difficult class of stochastic programs due
to its possible nondifferentiability and nonconvexity even with simple linear random …

Distributionally robust chance-constrained programs (DR-CCPs) over Wasserstein
ambiguity sets exhibit attractive out-of-sample performance and admit big-M–based mixed …

The detrimental consequences of accidents in the supply chain pose a major challenge to
the management of transportation risks in the hazardous products supply chain. The …

Chance constraints yield non-convex feasible regions in general. In particular, when the
uncertain parameters are modeled by a Wasserstein ball, arXiv: 1806.07418 and arXiv …

The increasing integration of renewable energy sources (RES) in power systems poses
challenges for peak shaving operations due to RES uncertainty. However, it is difficult to …

In this paper, we tackle the resolution of chance-constrained problems reformulated via
sample average approximation. The resulting data-driven deterministic reformulation takes …