The concepts of risk-aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. Statistical learning community has also …

This paper reviews recent advances in the field of optimization under uncertainty via a
modern data lens, highlights key research challenges and promise of data-driven …

The concepts of risk aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. The statistical learning community has …

We provide an exact deterministic reformulation for data-driven, chance-constrained
programs over Wasserstein balls. For individual chance constraints as well as joint chance …

Moment and polynomial optimization has received high attention in recent decades. It has
beautiful theory and efficient methods, as well as broad applications for various …

A challenge of planning real-life sustainable supplier selection and order allocation (SS/OA)
problems for purchasing companies is to gather the extensive data and exact distributions of …

We study joint chance constraints where the distribution of the uncertain parameters is only
known to belong to an ambiguity set characterized by the mean and support of the …

Bike-sharing systems are important components of urban transportation systems that
facilitate short-distance travel. In recent years, free-floating bike-sharing systems have …

Natural disasters not only inflict massive life and economic losses but also result in
psychological damage to survivors, at times even causing social unrest. It is necessary to …

We study a variant of the capacitated vehicle routing problem (CVRP), which asks for the
cost-optimal delivery of a single product to geographically dispersed customers through a …