We represent a closed-loop supply chain formed of one manufacturer and one retailer as a dynamic game played over an event tree, which naturally allows to ...

We consider a two-stage game in a differentiated duopoly, where firms can pursue both a financial and an environmental objective. We assume that the maximu...

Given a set of predefined duties and groups of drivers, the duty assignment problem with group-based driver preferences (DAPGDP) aims at building rosters tha...

We consider computationally expensive blackbox optimization problems and present a method that employs surrogate models and concurrent computing at the searc...

We study a new variant of the well-studied Vehicle Routing Problem with Time Windows (VRPTW), called the fragility-constrained VRPTW, which assumes that ...

Berth allocation and pilotage planning are the two most important decisions made by a seaport for serving incoming vessels. Traditionally, the berth allocati...

Scholars and practitioners have long recognised the importance of data-driven operations and supply chain management (OSCM), which typically centres on produ...

This work investigates lot-sizing with component substitution under demand uncertainty. The integration of component substitution with lot-sizing in an uncer...

We consider the problem of designing vehicle routes in a distribution system that are at the same time cost-effective and visually attractive. In this pape...

Generation expansion planning (GEP) is a classical problem that determines an optimal investment plan for existing and future electricity generation technolo...

This work introduces the StoMADS-PB algorithm for constrained stochastic blackbox optimization, which is an extension of the mesh adaptive direct-search (MAD...

This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm with the Cross-Entropy (CE) method for non smooth constrained optimizat...

In this paper, we propose an exact branch-price-and-cut (BPC) algorithm for the two-echelon vehicle routing problem with time windows. This problem arises i...

Demand response (DR) has been increasingly growing in significance among the solutions to tackle climate change, along with the development of intermittent r...

The Ninth Montreal IPSW took place on August 19-23, 2019, and was jointly organized by the CRM and IVADO (Institute for Data Valorization). The workshop welc...

We propose a new stochastic variance-reduced damped L-BFGS algorithm, where we leverage estimates of bounds on the largest and smallest eigenvalues of the He...

This paper studies disjunctive cutting planes in Mixed-Integer Conic Programming. Building on conic duality, we formulate a cut-generating conic program for...

Data acquisition and recording in the form of databases are routine operations. The process of collecting data, however, may experience irregularities, res...

This work reviews blackbox optimization applications over the last twenty years, addressed using direct search optimization methods. Emphasis is placed on...

Conditional estimation given specific covariate values (i.e., local conditional estimation or functional estimation) is ubiquitously useful with applications...