This paper studies the Dynamic Facility Location Problem with Modular Capacities (DFLPM). We propose a linear relaxation based heuristic (LRH) and an evoluti...

\(K\)-medoids clustering is among the most popular methods for cluster analysis, but it carries several assumptions about the nature of the latent clusters...

Suite aux travaux de Estrin et al. (2019), nous développons une méthode pour l’optimisation avec contraintes générales basée sur une fonction de pénalité d...

In large commercial airlines, the monthly schedule (roster) of the crew members is usually determined by solving two problems sequentially, namely, the crew ...

We consider a class of min-max robust problems in which the functions that need to be robustified can be decomposed as the sum of arbitrary functions. This...

We present a case study of using machine learning classification algorithms to initialize a large scale commercial operations research solver (GENCOL) in the...

Drawing on statistical learning theory, we derive out-of-sample and optimality guarantees about the investment strategy obtained from a regularized portfoli...

This paper considers a dynamic Emergency Medical Services (EMS) network design problem and introduces two novel two-stage stochastic programming formulatio...

Randomized decision making refers to the process of taking decisions randomly according to the outcome of an independent randomization device such as a dic...

We consider several time series and for each of them, we fit an appropriate dynamic parametric model. This produces serially independent error terms for each...

La méthode des résidus minimaux (MINRES) de Paige et Saunders (1975), qui est souvent la méthode privilégiée pour les systèmes linéaires symétriques, est une...

For nearest neighbor univariate random walks in a periodic environment, where the probability of moving depends on a periodic function, we show how to estim...

Given \(n\) points, a symmetric dissimilarity matrix \(D\) of dimensions \(n\times n\) and an integer \(p\geq 2\), the \(p\)-dispersion problem (pD...

Nous étudions l'évolution dans le temps d'une industrie oligopolistique, différenciée verticalement et horizontalement, où les entreprises d’un même groupe p...

In the Inventory Routing Problem customer demand is satisfied from inventory which is replenished with capacitated vehicles. The objective is to minimize tot...

Computational speed and global optimality are a key need for pratical algorithms of the OPF problem. Recently, we proposed a tight-and-cheap conic relaxation...

Multi-agent reinforcement learning has made significant progress in recent years, but it remains a hard problem. Hence, one often resorts to developing lea...

Nous proposons une méthode itérative pour la résolution de systèmes de point de selle symétriques qui exploite la tridiagonalisation orthogonale de Saunders,...

Nous proposons une méthode de régularisation pour les problèmes aux moindres carrés non linéaires avec contraintes d'égalité. Notre appliquons les approches...

In demand-response programs, aggregators balance the needs of generation companies and end-users. This work proposes a two-phase framework that shaves the ag...