Significant progress has been made in the field of computer vision, due to the development of supervised machine learning algorithms, which efficiently extra...

L’accroissement de la proportion d’énergies renouvelables fluctuantes représente un défi important pour les exploitants de réseaux électriques. Il existe p...

We consider three colouring problems which are variations of the basic vertex-colouring problem, and are motivated by applications from various domains. We g...

Reducing the number of features used in data classification can remove noisy or redundant features, reduce the cost of data collection, and improve the accur...

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...

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...

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...

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 assistons présentement à une accélération dans le développement des énergies renouvelables raccordées aux réseaux électriques. En raison des fluctuati...

Recommender systems make use of different sources of information for providing users with recommendations of items. Such systems are often based on collabor...

Operations Research (OR) has a very important role to play in credit scoring for building models that can help the lending organization to make a good decisi...

Algorithms for finding sparse solutions of underdetermined systems of linear equations have been the subject of intense interest in recent years, sparked b...

In this paper, we propose an intuitive way to couple several dynamic time series models even when there are no innovations. This extends previous work for m...

The airline crew scheduling problem involves determining schedules for airline crew members such that all the scheduled flights over a planning horizon (usua...

This paper investigates the current patient transportation between services in a large hospital and provides a simulation-optimization solution to reduce com...

Multiple-point simulations have been introduced over the past decade to overcome the limitations of second-order stochastic simulations in dealing with geolo...

A new non-stationary, high-order sequential simulation method is presented herein, aiming to accommodate complex curvilinear patterns and high-order spatia...