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 purpose of the present note is to bring clarifications to certain concepts and surrounding notation of Aravkin et al. (2022). All results therein contin...

This paper develops an efficient hybrid algorithm to solve the credit scoring problem. We use statistical mathematical programming to develop new classificat...

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...

We develop a trust-region method for minimizing the sum of a smooth term \(f\) and a nonsmooth term \(h\), both of which can be nonconvex. Each iteratio...

In this paper, we study the pickup and delivery problem with time windows and multiple compartments (PDPTWMC). The PDPTWMC generalizes the pickup and delive...

To cover the import taxes, a manufacturer typically charges a higher price in a foreign market than in its domestic market. The price difference can lead to ...

This paper presents <code>FluxNLPModels.jl</code> and <code>KnetNLPModels.jl</code>, new Julia packages enabling a neural network, modelled with either Flux....

The Quadratic Knapsack Problem (QKP) is a combinatorial optimization problem that has attracted much attention over the past four decades. In this problem, o...

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 ...

We propose new algorithms with provable performance for online binary optimization subject to general constraints and in dynamic settings. We consider the su...

We consider a firm offering an opaque good over one selling season, that is, a product whose full characteristics are only revealed after the consumer comp...

We present a Julia framework dedicated to partially-separable problems whose element function are detected automatically. This framework takes advantage of ...

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...