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...

We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, ...

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...

High-order sequential simulation methods have been developped as an alternative to existing frameworks to facilitate the modelling of spatial complexity of...

In this paper, we develop algorithmic approaches for a recently defined class of games, the integer programming games. Two general methods to approximate an...

Top-tier customers -that is, those 20% of customers that typically bring in 80% of all profits- are extremely valuable to companies. In the many instances ...

Genetic algorithms are used for feature selection through a fitness function that drives the evolution of populations. With parallel universes, an importance...