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.
Authors: Maryam Daryalal, Ayse N. Arslan, Merve Bodur
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: 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]
Authors: Ayse N. Arslan, Michael Poss
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: 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]
Authors: Luis Marques, François Clautiaux, Aurélien Froger
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 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]
Authors: Xuan Ren, Aurélien Froger, Ola Jabali, Gongqian Liang
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: 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]
Authors: Brais González-Rodrı́guez, Aurélien Froger, Ola Jabali, Joe Naoum-Sawaya
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: 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]
Authors: Ayse N. Arslan, Jeremy Omer, Fulin Yan
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: 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]
This thesis focuses on algorithmic design for three combinatorial optimization problems related to transportation, logistics and production research with specific types of indus- trial constraints. First, we consider the Precedence Constrained Generalized Traveling Salesman Problem (PCGTSP). This problem is an extension of two well-known combinatorial optimization problems — the Generalized Traveling Salesman Problem (GTSP) and the Precedence Constrained Asymmetric Traveling Salesman Problem (PCATSP), whose path version is known as the Sequential Ordering Problem (SOP).
[Read more]
Authors: François Clautiaux, Siham Essodaigui, Alain Nguyen, Ruslan Sadykov, Nawel Younes
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: 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]
Authors: Najib Errami, Eduardo Queiroga, Ruslan Sadykov, Eduardo Uchoa
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: 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]
Authors: Xavier Blanchot, François Clautiaux, Aurélien Froger, Manuel Ruiz
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 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]
Authors: Maryam Daryalal, Ayse N. Arslan, Merve Bodur
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]
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]