We are pleased to announce that a permanent associate professor position (maître de conférences) at the University of Bordeaux is available for the 2025 national recruitment campaign. The successful candidate will join the Edge team.
[Read more]We are happy to announce that Paul Archipczuk has joined our team as an engineer. Paul will work on the project Grip4all about robotic palletizing of heterogeneous products without prior scheduling.
We are happy to announce that Pierre Pinet has joined our team as a CIFRE PhD student with Saint-Gobain. Pierre will work on solving routing problems under uncertainty.
Abstract: Mixed-integer linear programming (MILP) has become a cornerstone of operations research. This is driven by the enhanced efficiency of modern solvers, which can today find globally optimal solutions within seconds for problems that were out of reach a [Read more]
Abstract: In this paper, we propose a new set-partitioning model for the two-echelon vehicle routing problem with drones (2E-VRP-D), where partial routes corresponding to drone movements are enumerated using an efficient dynamic program. To solve the model we [Read more]
We are happy to announce that Mariam Sangare has joined our team as a postdoctoral researcher. Mariam will work on the EDF-Inria Challenge on generation expansion planning problems. Prior to her arrival in the team Mariam has completed her PhD thesis at University of Montpellier under the supervision of Michael Poss.
Abstract: In this work, we design primal and dual bounding methods for multistage adaptive robust optimization (MSARO) problems motivated by two decision rules rooted in the stochastic programming literature. From the primal perspective, this is achieved by ap [Read more]
Abstract: Uncertainty reduction has recently been introduced in the robust optimization literature as a relevant special case of decision-dependent uncertainty. Herein, we identify two relevant situations in which the problem is polynomially solvable. We provi [Read more]
Abstract: We study the problem of designing a cabinet made up of a set of shelves that contain compartments whose contents slide forward on opening. Considering a set of items candidate to be stored in the cabinet over a given time horizon, the problem is to d [Read more]
Abstract: We propose a heuristic algorithm capable of handling multiple variants of the vehicle routing problem with drones (VRPD). Assuming that the drone may be launched from a node and recovered at another, these variants are characterized by three axes, (1 [Read more]
Abstract: Establishing the size of an EV fleet is a vital decision for logistics operators. In urban settings, this issue is often dealt with by partitioning the geographical area around a depot into service zones, each served by a single vehicle. Such zones u [Read more]
Abstract: The kidney exchange problem (KEP) is an increasingly important healthcare management problem in most European and North American countries which consists of matching incompatible patient-donor pairs in a centralized system. Despite the significant pr [Read more]
Abstract: In this work, we study optimization problems where some cost parameters are not known at decision time and the decision flow is modeled as a two-stage process within a robust optimization setting. We address general problems in which all constraints [Read more]
We are happy to announce that Najib Errami has joined our team as an engineer. Najib will work on the project ADLib which aims to create a library for Aggregation/Disaggregation of large network flow models.
Abstract: In this paper, we consider a new industrial problem, which occurs in the context of the automobile industry. This problem occurs during the testing phase of a new vehicle. It involves determining all the variants of the vehicle to be manufactured in [Read more]
Abstract: The optimization community has made significant progress in solving Vehicle Routing Problems (VRPs) to optimality using sophisticated Branch-Cut-and-Price (BCP) algorithms. VRPSolver is a BCP algorithm with excellent performance in many VRP variants. [Read more]
Abstract: In this paper, we study how a regulatory constraint limiting a measure of unserved demand, called Loss Of Load Expectation (LOLE), can be incorporated into a strategic version of a stochastic generation and transmission expansion planning problem. Th [Read more]
Abstract: In this work, we design primal and dual bounding methods for multistage adjustable robust optimization (MSARO) problems motivated by two decision rules rooted in the stochastic programming literature. From the primal perspective, this is achieved by [Read more]