This paper first introduces a computationally efficient approach for conducting a time-series impact analysis of electric vehicle (EV) charging on the loadin...

Station-based Bike-sharing systems have been implemented in multiple major cities, offering a low-cost and environmentally friendly transportation alternativ...

This paper addresses risk averse constrained optimization problems where the objective and constraint functions can only be computed by a blackbox subject to...

We study the integration of multi-period assignment, routing, and scheduling of care workers for home health care services. In such a context, it is importa...

Two-stage stochastic programs are a class of stochastic problems where uncertainty is discretized into scenarios, making them amenable to solution approaches...

We investigate counterparty credit risk and credit valuation adjustments in portfolios including derivatives with early-exercise opportunities, under a net...

Benders decomposition has been applied significantly to tackle large-scale optimization problems with complicating variables, which, when temporarily fixed, ...

Recommender systems provide personalized recommendations to their users for items and services. They do that using a model that is tailored to each user to i...

This paper presents a study on the best possible use of optimization models for the short-term hydropower scheduling problem. Different deterministic and sto...

The emerging demand for electric bicycles in recent years has prompted several bike-sharing systems (BSS) around the world to adapt their service to a new wa...

The popularity of bike-sharing systems has constantly increased throughout the last years. Most of such success can be attributed to their multiple benefits,...

We consider the problem of minimizing the linear cost of multistate homogeneous series-parallel system given the nonlinear reliability constraint on the syst...

Recently there has been a surge of interest in operations research~(OR) and the machine learning~(ML) community in combining prediction algorithms and optimi...

This paper studies linear-quadratic Stackelberg games with a major player (leader) and \(N\) minor players (followers). To design decentralized strategies ...

This work considers stochastic optimization problems in which the objective function values can only be computed by a blackbox corrupted by some random noise...

We investigate a facility location problem with modular capacity under demand uncertainty arising at Hydro-Québec, the largest public utility in Canada. We p...

This paper introduces the consistent vehicle routing problem with stochastic customers and demands. We consider driver consistency as customer-driver assignm...

Optimizing static risk-averse objectives in Markov decision processes is challenging because they do not readily admit dynamic programming decompositions. Pr...

Seaports are highly vulnerable to climate-change induced events, which makes it necessary for them to invest in climate change adaptation measures to ensure ...

For planning the operation of power transmission systems, which transport the energy produced by generation plants to customers centers, it is essential to e...