A large number of problems involve making decisions in an uncertain environment and,
hence, with unknown outcomes. Optimization models aimed at controlling the trade‐off …

Many industries use revenue management to balance uncertain, stochastic demand and
inflexible capacity. Popular examples include airlines, hotels, car rentals, retailing, and …

Currently, stochastic optimization on the one hand and multi-objective optimization on the
other hand are rich and well-established special fields of Operations Research. Much less …

Faults on overhead power line infrastructures in electric power distribution systems (DSs)
can potentially ignite catastrophic wildfires, especially in areas exposed to high wind …

Future distribution systems will accommodate an increasing share of distributed energy
resources (DERs). Facing with this new reality, virtual power plants (VPPs) play a key role to …

Recent research on optimal power flow (OPF) in networks with renewable power involves
optimizing both first and second stage variables that adjust the decision once the uncertainty …

This paper focuses on simulation-based approaches for estimating systemic risk measures.
In particular, we provide the asymptotic forms of the relative errors for widely used systemic …

The risk-triplet approach pioneered by Kaplan and Garrick is the keystone of operational risk
analysis. We perform a sharp embedding of the elements of this framework into the one of …

We introduce a new class of distributionally robust optimization problems under decision-
dependent ambiguity sets. In particular, as our ambiguity sets, we consider balls centered on …

Chance-constrained programming (CCP) is one of the most difficult classes of optimization
problems that has attracted the attention of researchers since the 1950s. In this survey, we …