7.1.1 GroupTesting

• Keywords:
  Linear optimization, Group Testing, Graph algorithmics
• Functional Description:

  Group testing is a screening strategy that involves dividing a population into several disjoint groups of subjects. In its simplest implementation, each group is tested with a single test in the first phase, while in the second phase only subjects in positive groups, if any, need to be tested again individually.

  To contribute to the effort to tackle the COVID-19 sanitary crisis, we developed this software which allows to create groups of individuals to test via the group testing technique while minimizing a linear combination of the expected number of false negative and false positive classifications.

  The test design problem is modeled as a constrained shortest path problem on a specific graph and we design and implement an ad hoc algorithm to solve this problem. We validate the algorithm on instances based on Santé Publique France data on COVID-19 screening tests.

• Contact:
  Frederic Semet

7.1.2 INOCSBox

• Keywords:
  Linear optimization, Operational research, Toolbox
• Functional Description:

  This software is a toolbox that contains algorithms that are frequently used to solve optimization problems tackled by (but not only) the team.

  The objective of the toolbox is to contain a set of code skeletons that allow researchers to integrate adequate data structures and basic algorithms for different structures complexity that appears in the optimization problems we study. The current version of the toolbox contains classical heuristic tools (generic local search) to solve, among others, the vehicle rouring problem and its variants. It also contain a code to exactly and heuristically solve the Shortest Path Problem with Ressource Constraints that is usually encountered in the resolution of problem with Branch-and-Price algorithms.

  The future objective is to include automatic reformulation tools for bi-level optimization problems and state-of-the-art codes for the development of decomposition methods.

• Contact:
  Tifaout Almeftah

8.1.1 Telecommunication and network optimization.

Several classes of models have been proposed in the literature for the Steiner tree problem with hop constraints. One class is characterized by having hop‐indexed arc variables. Although such models have proved to have a very strong linear programming bound, they are not easy to use because of the huge number of variables. This has motivated some studies with models involving fewer variables that use, instead of the hop‐indexed arc variables, hop‐indexed node variables. We contextualized the linear programming relaxation of these node‐based models in terms of the linear programming relaxation of known arc‐based models. We showed that the linear programming relaxation of a general node‐based model is implied by the linear programming relaxation of a straightforward arc‐based model 17.

8.1.2 Logistics and warehouse management.

Picking is the process of retrieving products from inventory. It is considered the most expensive of warehouse management operations. In INOCS, we addressed the Joint Order Batching and Picker Routing Problem (JOBPRP) that is a challenging optimization problem with two integrated decisions: customer orders are grouped into batches (order batching problem) that are collected by pickers who travel the shortest possible distance (picker routing problem). Human pickers often perform picking, so we proposed to explicitly consider human factors in the JOBPRP, by first studying the consideration of congestion effects when several pickers share the same space at the same time 42, 31. These congestion situations are really stressful for the pickers, and considering them in mathematical models is really challenging since a temporal aspect must be included.

We also started to address an extension of the JOBPRP that includes the sequencing question, i.e. the additional assignment and sequencing of batches for each picker to meet the required deadlines of orders. We show that a bin-packing formulation permits solving the problem with a column generation approach efficiently 32.

Another relevant problem we study in INOCS is the Operational Storage Location Assignment Problem, which asks to optimize the location of products in warehouses to minimize the distance walked by the picker 27.

8.1.3 Logistics network design problem.

Planning transportation operations within a supply chain is a difficult task often outsourced to logistics providers. At the tactical level, the problem of distributing products through a multi-echelon network is defined in the literature as the Logistics Service Network Design Problem (LSNDP). To solve the LSNDP, we propose a solution approach based on Benders decomposition. In a previous paper   58, we proposed an enhanced Benders decomposition algorithm for solving the LSNDP, which consists in strengthening the master problem with variables and constraints that model the need to route a super-product derived from the aggregation of all the products to be transported. We developed a more elaborated algorithmic strategy that exploits this partial Benders decomposition by intelligently varying the amount of subproblem information used to formulate the master problem. We refer to this strategy as Meta Partial Benders Decomposition (Meta-PBD). Meta-PBD operates in two steps, with the first aiming to explore different areas within the feasible region of the original problem and to quickly determine high-quality solutions. To do so, the number of super-products used to formulate the master problem changes dynamically while respecting a threshold value to ensure computational tractability. Next, a second phase aims to close the optimality gap. This second phase increases the amount of subproblem information used to formulate the master problem, such that the latter becomes provably equivalent to the original problem. While this master problem is computationally challenging, high-quality solutions generated through the first phase enable many nodes of the resulting branch-and-bound search tree to be pruned, accelerating convergence  12.

8.1.4 Complex routing problems.

Vehicle Routing Problems (VRPs) are classical optimization problems in transportation and logistics. In INOCS, we address complex routing problems generalizing the VRP or combining the VRP with another optimization problem. We studied an extension of the VRP in a context where customers require several commodities that can be transported in the same vehicle, and each customer is allowed to be visited multiple times. However, the demand for a single commodity must be delivered by one vehicle only. The problem is coined as the Commodity constrained Split Delivery VRP (C-SDVRP). We developed a heuristic column generation with performance guarantee to solve the C-SDVRP 37. We also studied an extension of the C-SDVRP in a two-echelon context and multiple intermediate depots. The first echelon considers collecting several commodities with direct trips while the second is a multi-depot version of the C-SDVRP. To solve this complex problem, we first proposed a generic sequential approach with a comparison of different strategies 18. Then, we also developed an exact branch-price-and-cut algorithm to solve the problem 39.

Another extension of the VRP that we addressed is an integrated production scheduling problem and multi-trip VRPTW, where the products have a limited lifespan so they have to be delivered shortly after their production. Hence, the scheduling and the routing problems are really interrelated, and finding feasible solutions with a sequential approach is not trivial. This problem finds an application in home chemotherapy with a limited lifespan of the drugs. To solve this problem, we developed a dedicated large neighborhood search approach where production and routing sequences are iteratively modified while a linear program is used to determine optimal start times of the production and routing tasks 44.

Last, we explore the operational planning and the real-time management of a fleet of highly automated agriculture vehicles that perform tasks throughout multiple fields potentially owned by different farmers and/or enterprises. In this context, the concepts of fairness and equity must be considered to balance the execution of tasks between vehicles and also between farmers. We studied new variants of the operational planning problem that maximize utilitarian, egalitarian, and elitist social welfare and balance workload and efficiency of the fleet  26.

8.1.5 Public transportation networks.

Infrastructure network design constitutes a major step in the planning of a transportation network whose purpose is to improve the mobility of the inhabitants of a city or metropolitan area. In the area of passengers transportation, the aim is to get the infrastructure close to potential customers. In this case, one might select a sub(network) from an underlying network to capture or cover as much traffic for a reasonable construction cost. The paper 14 is devoted to this problem, and considers the Maximum Covering Network Design Problem (MC) as well as the closely related Partial Covering Network Design Problem (PC), in which one minimizes the network design cost for building the network under the constraint that a minimum percentage of the total traffic demand is covered. Models for problems (MC) and (PC), as well as exact methods based on Benders decomposition are provided and compared through computational experiments.

8.1.6 Machine learning application.

Feature selection is an important issue to avoid overfitting when applying a support vector machine (SVM) approach. The classical SVM model minimizes a compromise between the structural risk and the empirical risk. In 11, we consider the Support Vector Machine with feature selection and we design and implement a bi-objective evolutionary algorithm for approximating the Pareto optimal frontier of the two objectives.

8.2.1 Strategic bidding in price coupled regions.

With the emerging deregulated electricity markets, a part of the electricity trading takes place in day-ahead markets where producers and retailers place bids in order to maximize their profit. We present a price-maker model for strategic bidding from the perspective of a producer in Price Coupled Regions (PCR) considering a capacitated transmission network between local day-ahead markets. The aim for the bidder is to establish a production plan and set its bids taking into consideration the reaction of the market. We consider the problem as deterministic, that is, the bids of the competitors are known in advance. We are facing a bilevel optimization problem where the first level is a Unit Commitment problem, modeled as a Mixed Integer Linear Program (MILP), and the second level models a market equilibrium problem through a Linear Program. The problem is first reformulated as a single level problem. Properties of the optimal spot prices are studied to obtain an extended formulation that is linearized and tightened using new valid inequalities. Several properties of the spot prices allow to reduce significantly the number of binary variables. Two novel heuristics are proposed 13.

8.2.2 Equilibrium analysis of risk-hedging strategies in decentralized electricity markets.

In 52, we investigate equilibrium problems arising in various decentralized designs of the electricity market involving risk-averse prosumers. The prosumers have the possibility to hedge their risks through financial contracts that they can trade with peers or purchase from an insurance company. We build several market designs of increasing complexity, from a one-stage market design with inter-agent financial contract trading to a Stackelberg game where an insurance company acts as a leader and prosumers are followers. We derive risk-hedging pricing scheme for each model and show that the Stackelberg game pessimistic formulation might have no solution. We propose an equivalent reformulation as a parametrized generalized Nash equilibrium problem, and characterize the set of equilibria. We prove that the insurance company can design price incentives that guarantee the existence of a solution of the pessimistic formulation, which is $\epsilon$ close to the optimistic one. We then derive economic properties of the Stackelberg equilibria such as fairness, equity, and efficiency. We also quantify the impact of the insurance company incomplete information on the prosumers’ risk-aversion levels on its cost and social cost.

8.2.3 Bilevel location problems.

We consider the problem faced by a retail chain that must select what mutual-substitute items to display in each one of its stores to maximize revenues. The number of items cannot exceed the limit space capacity of each store. Customers purchase the one product that maximizes their utility, which depends on the product price, travel cost to the store, and reservation price, known to the retailer. The retailer solves a mixed-integer bilevel optimization problem, which can be formulated as a single-level optimization problem. In  16, we propose Branch and Cut and Cut and Branch methods and include a family of valid inequalities to solve the problem.

8.2.4 Equilibrium Learning in strategic resource pricing games

In 15, we consider a marketplace in the context of 5G network slicing, where Application Service Providers (ASP), i.e., slice tenants, providing heterogeneous services, are in competition for the access to the virtualized network resource owned by a Network Slice Provider (NSP), who relies on network slicing. We model the interactions between the end users (followers) and the ASPs (leaders) as a Stackelberg game. We prove that the competition between the ASPs results in a multi-resource Tullock rent-seeking game. To determine resource pricing and allocation, we devise two innovative market mechanisms. First, we assume that the ASPs are pre-assigned with fixed shares (budgets) of infrastructure, and rely on a trading post mechanism to allocate the resource. Under this mechanism, the ASPs can redistribute their budgets in bids and customise their allocations to maximize their profits. In case a single resource is considered, we prove that the ASPs’ coupled decision problems give rise to a unique Nash equilibrium. Second, when ASPs have no bound on their budget, we formulate the problem as a pricing game with coupling constraints capturing the shared resource finite capacities, and derive the market prices as the duals of the coupling constraints. In addition, we prove that the pricing game admits a unique variational equilibrium. We implement two online learning algorithms to compute solutions of the market mechanisms. A third fully distributed algorithm based on a proximal method is proposed to compute the Variational equilibrium solution of the pricing game. Finally, we run numerical simulations to analyse the market mechanism’s economic properties and the convergence rates of the algorithms.

8.3.1 Deciding feasibility of a booking in the European Gas Market.

During the last decades, the European gas market has undergone ongoing liberalization, resulting in the so-called entry-exit market system. The main goal of this market reorganization is the decoupling of trading and actual gas transport. To achieve this goal within the European entry-exit market, gas traders interact with transport system operators (TSOs) via bookings and nominations. A booking is a capacity-right contract in which a trader reserves a maximum injection or withdrawal capacity at an entry or exit node of the TSO’s network. On a day-ahead basis, these traders are then allowed to nominate an actual load flow up to the booked capacity. To this end, the traders specify the actual amount of gas to be injected to or withdrawn from the network such that the total injection and withdrawal quantities are balanced. On the other hand, the TSO is responsible for the transport of the nominated amounts of gas. By having signed the booking contract, the TSO guarantees that the nominated amounts can actually be transported through the network. More precisely, the TSO needs to be able to transport every set of nominations that complies with the signed booking contracts. Thus, an infinite number of possible nominations must be anticipated and checked for feasibility when the TSO accepts bookings. As a consequence, the entry-exit market decouples trading and transport. However, it also introduces many new challenges, e.g. the checking of feasibility of bookings or the computation of bookable capacities on the network.

In  21, we consider networks with linearly modeled active elements such as compressors and control valves that do not lie on cycles of the network. Since these active elements allow the TSO to control the gas flow, the single-level approaches from the literature are no longer applicable. We thus present a bilevel approach to decide the feasibility of bookings in networks with active elements. Besides the classical Karush–Kuhn–Tucker reformulation, we obtain three problem-specific optimal-value-function reformulations, which also lead to novel characterizations of feasible bookings in active networks. We compare the performance of our methods by a case study based on data from the GasLib.

8.3.2 Mixed-Integer Quantile Minimization Problems.

In this work we consider mixed-integer linear quantile minimization problems that yield large-scale problems that are very hard to solve for real-world instances. We motivate the study of this problem class by two important real-world problems: a maintenance planning problem for electricity networks and a quantile-based variant of the classic portfolio optimization problem. For these problems, we develop valid inequalities and present an overlapping alternating direction method. Moreover, we discuss an adaptive scenario clustering method for which we prove that it terminates after a finite number of iterations with a global optimal solution. We study the computational impact of all presented techniques and finally show that their combination leads to an overall method that can solve the maintenance planning problem on large-scale real-world instances provided by the EURO/ROADEF challenge 2020 and that they also lead to significant improvements when solving a quantile-version of the classic portfolio optimization problem 46.

8.3.3 Transaction fees optimization in the Ethereum blockchain.

In blockchains, transaction fees are fixed by the users. The probability for a transaction to be processed quickly increases with the fee level. We studied the transaction fee optimization problem in the Ethereum blockchain. This problem consists of determining the minimum price a user should pay so that its transaction is processed with a given probability in a given amount of time. To reach this goal, we define a new solution method based on a Monte Carlo approach to predict the probability that a transaction will be mined within a given time limit. Numerical results on real data highlight the quality of the results 19.

8.3.4 Balancing efficiency and privacy in a decision-dependent network game.

We consider a network game, where End Users (EUs) minimize their cost by computing their demand and generation while satisfying a set of local and coupling constraints. Their nominal demand constitutes sensitive information, that they might want to keep private. We prove that the network game admits a unique Variational Equilibrium, which depends on the private information of all the EUs. A data aggregator is introduced, which aims to learn the EUs’ private information. The EUs might have incentives to report biased and noisy readings to preserve their privacy, which creates shifts in their strategies. Relying on performative prediction, we define a decision-dependent game $G^{\mathrm{stoch}}$ to couple the network game with a data market. Two variants of the Repeated Stochastic Gradient Method (RSGM) are proposed to compute the Performatively Stable Equilibrium solution of $G^{\mathrm{stoch}}$, that outperform RSGM with respect to efficiency gap minimization, privacy preservation, and convergence rates in numerical simulations 54. Convergence proofs of the algorithms will be detailed in further work, and rely on stochastic approximation theory.

10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an Inria International Program

10.1.2 Participation in other International Programs

10.2.1 Visits of international scientists

10.2.2 Visits to international teams

10.3.1 Horizon Europe

CHIST-ERA SEC-OREA project: “Supporting Energy Communities-Operational Research and Energy Analytics”. (2020 – 2023) SEC-OREA aims to enable local energy communities (LECs) to participate in the decarbonisation of the energy sector by developing advanced efficient algorithms and analytics technologies.

Partners: INRIA- INOCS (France), Université Libre de Bruxelles (Belgique), Uuniversity college Dublin (Ireland), Riga technical University (Lithuania)

10.4.1 ANR

ANR project AGIRE (2020-2024) – Decision system for smart management of resources in warehouses.

In collaboration with Ecole des Mines de Saint-Etienne (Gardanne), IFSTTAR (Champs-sur-Marne), HappyChic (Tourcoing).

This project addresses human resources management in warehouses which supply either sale points (B2B) or final consumers (B2C). Nowadays, such warehouses are under pressure. This is mainly due to the no inventory policy at the sale points and to the constant growth of e-commerce sales in France and Europe. In terms of logistics, this translates into an increasing number of parcels to prepare and to ship to satisfy an order, which is known typically a few hours before. Moreover, the total number of products to be packed varies very significantly from day-to-day by a factor of at least 3.

The novelty of the project is twofold: (1) The human factor is explicitly be taken into account. It is integrated in the mathematical models and algorithms that are developed for the project. The aim is to improve the quality of employees' work ensuring the efficiency of the logistic system; (2) Problems at different decision levels are integrated and tackled jointly. At the tactical level, the main issues are workload smoothing and the management of the storage zone. At operational level, the major issues concern the rearrangement of the picking zone, the picking tours, and the dynamic reorganization of activities to manage uncertainties.

ANR project ADELE (2022-2025): “Resource Allocation in City Logistics with Demand Uncertainty” in collaboration with LCOMS (Univ. of Lorraine), Toulouse Business School, Colisweb. A central issue in city logistics (CL) is to design logistics systems that move goods to, from, and within urban areas while meeting sustainability goals. A central role is played by the orchestrator. The orchestrator is the stakeholder that operates and organizes a CL system when multiple stakeholders are implied. In ADELE, we tackle the planning problem faced by the orchestrator in coordinating and managing the resources offered by carriers or logistics service providers. The problem aims to determine what logistics facilities should be used and when and where the vehicles of the carriers should be assigned to cover the demand in the most efficient way. A key feature is that demand is uncertain. We consider two main variants depending on whether the CL system is one or two tiers. ADELE aims to develop new efficient mathematical models and decision support methods. we aim to design and implement ad-hoc optimization algorithms based on mathematical modeling. This project is a continuation of the INRIA Innovation Lab Colinocs.

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

11.1.3 Journal

11.1.4 Invited talks

• Plenary speaker at French, German, Portuguese Optimization Conference, Porto, May 2022, Luce Brotcorne

11.1.5 Leadership within the scientific community

• Informs, Energy Natural Resources and the Environment Section, Luce Brotcorne, Secretary-Treasurer, 2022-2024.
• EURO Working Group "Pricing and Revenue Management": Luce Brotcorne - coordinator.
• PGMO, Fondation Gaspard Monge: Luce Brotcorne - Member of the scientific committee.
• EURO Working Group "European Network Optimization Group (ENOG)": Bernard Fortz - coordinator.
• EURO Working Group "Vehicle routing and logistics optimization (VEROLOG)": Frédéric Semet - Member of the board.
• SIAG/Optimization Prize committee: Martine Labbé - Chair.
• ORBEL (Belgian Operations Research Society): Bernard Fortz - Member of the administration board.
• ORBEL representative for EURO: Bernard Fortz
• CNRS GdR 3002 : Operations Research: Frédéric Semet - Member of the steering committee

11.1.6 Scientific expertise

• ANID, Chile Evaluation Group: Luce Brotcorne.
• Scientific committee of France-Netherlands Exchange Program: Luce Brotcorne - Member.
• NSERC Evaluation Group 1509: Bernard Fortz.
• INFORMS, ENRE, Early Career Best Paper award, president of the commission: Luce Brotcorne.
• Evaluation committee for INRIA/MITACS Exchange Program: Luce Brotcorne - Member.
• Evaluation committee COST GTRI: Luce Brotcorne - Member.
• President of the FRIA PE1 - jury 1: Bernard Fortz - Chair.
• Scientific orientation committee of the Interuniversity Centre on Entreprise Networks, Transportation and Logistics (CIRRELT), Canada: Bernard Fortz, Frédéric Semet - Members.
• Internal selection committee of Logistics in Wallonia : Bernard Fortz - Member.
• Selection committee for the ORBEL award for the best OR thesis: Bernard Fortz, Martine Labbé.
• Member of the PE6 panel for the evaluation of ERC Consolidator grants : Martine Labbé
• Scientific Advisory Board of IWR and its Graduate school HGS MathComp, Heidelberg University: Martine Labbé - Member.
• Centro de Matemática, Aplicaçoes Fundamentais e Investigaçao Operacional, University of Lisbon: Martine Labbé - Member.
• IVADO International consultative committee, Montreal, Canada: Martine Labbé
• Selection committee for the SEIO-BBVA Awards: Martine Labbé.
• Selection committee for the prize Jean-Jacques Moreau from the Société Mathématique de France: Martine Labbé.
• Panel member for the Research Council of Norway: Frédéric Semet.

11.1.7 Research administration

• Deputy-director of CRIStAL: Frédéric Semet.
• Elected member of the Scientific Council of Centrale Lille: Diego Cattaruzza.
• Member of the OPTIMA Scientific Council: Diego Cattaruzza.

11.2.1 Teaching

• Master: Bernard Fortz, Recherche Opérationnelle et Applications, 30hrs, M1, University of Mons (Charleroi campus), Belgium.
• Master: Bernard Fortz, Continuous Optimization, 24hrs, M1 & M2, Université libre de Bruxelles, Belgium.
• Master: Frédéric Semet, Supply Chain Management, 30hrs, M2, Centrale Lille.
• Master: Frédéric Semet, Operations Research, 28hrs, M2, Centrale Lille.
• Master: Luce Brotcorne, Optimisation, 14hrs, M1, Polytech Lille.
• Master: Luce Brotcorne, Recherche opérationnelle, 16hrs, M1 apprentissage, Polytech Lille.
• Master: Diego Cattaruzza, Frédéric Semet, Prescriptive analytics and optimization, 64hrs, M1, Centrale Lille.
• Master: Diego Cattaruzza, Object-Oriented Programming, 48hrs, M1, Centrale Lille.
• Master: Diego Cattaruzza, Operations Research, 16hrs, M1, Centrale Lille.
• Licence: Diego Cattaruzza, Maxime Ogier, Object-Oriented Programming, 40hrs, L3, Centrale Lille.
• Licence: Frédéric Semet, Advanced programming and Complexity, 24hrs, L3, Centrale Lille.
• Licence: Diego Cattaruzza, Maxime Ogier, Object-Oriented Programming, 44hrs, L2, Centrale Lille.
• Licence: Bernard Fortz, Algorithmique 1, 12hrs, L1, Université libre de Bruxelles, Belgium.
• Licence: Bernard Fortz, Algorithmique et Recherche Opérationnelle, 24hrs, L3, Université libre de Bruxelles, Belgium.

11.2.2 Supervision

• PhD completed: Luis Alberto Salazar Zendeja, Models and algorithms for network interdiction problems, December 2022, Diego Cattaruzza, Martine Labbé, Frédéric Semet.
• PhD in progress: Matteo Petris, Column generation approaches for integrated operationnal problems, from October 2019, Diego Cattaruzza, Maxime Ogier, Frédéric Semet.
• PhD in progress: Ilia Shilov, Algorithmic game and distributed learning for peer-to-peer energy market, from December 2019, Hélène Le Cadre, Ana Busic (Inria/ENS Paris), Goncalo Terca (VITO).
• PhD in progress: Thibault Prunet, Models and algorithm for tactical problems in warehouses with human factor considerations, from February 2020, Nabil Absi (Ecole des Mines de Saint Etienne), Valeria Borodin (Ecole des Mines de Saint Etienne), Diego Cattaruzza.
• PhD in progress: Natividad Gonzales Blanco, Exact and heuristic approaches for network design problems, from 2020, Bernard Fortz, Martine Labbé, Juan Antonio Mesa Lopez-Colmenar (University of Sevilla, Spain).
• PhD in progress: Moises Rodriguez Madrena, Design problems in continous spaces with different norms, from 2020, Bernard Fortz, Martine Labbé, Justo Puerto (University of Sevilla, Spain).
• PhD in progress: Pablo Torrealba Gonzalez, Batching and picker routing problems in warehouses taking into account human factors, from February 2021, Dominique Feillet (Ecole des Mines de Saint Etienne), Maxime Ogier, Frédéric Semet.
• PhD in progress: Cristian Aguayo, Supporting Energy Communities - Operational Research and Energy Analytics, from July 2021, Bernard Fortz.
• PhD in progress: Wenjiao Sun, Integrated optimization algorithms for routing and scheduling problems, from October 2021, Maxime Ogier, Frédéric Semet.
• PhD in progress: Luis Pablo Rojo, Incentive mechanisms for electric vehicle charging, from October 2021, Luce Brotcorne, Michel Gendreau (Polytehcnique Montréal, Canada), Miguel Anjos (University of Edinburgh, UK).
• PhD in progress: Haider Ali,Optimal techniques for charging autonomous electric vehicles with renewable energy sources, from October 2021, Luce Brotcorne, Bruno François (Centrale Lille).
• PhD in progress: Clement Legrand, Integration of machine learning into multi objective optimization problems, from October 2021, Marie-Eleonore Kessaci (Ecole Polytechnique de Lille), Laetitia Jourdan (Université de Lille), Diego Cattaruzza.
• PhD in progress: Juan Sepulveda, New optimization models and algorithms for local energy communities, from December 2021, Luce Brotcorne, Hélène Le Cadre.
• PhD in progress: Tifaout Almeftah, Models and algorithms for group testing, from December 2021, Diego Cattaruzza, Martine Labbé, Frédéric Semet.

11.2.3 Juries

• Xavier Blanchot, PhD, Université de Bordeaux, Résolution de problèmes d'optimisation stochastique de grande taille: application à des problèmes d'investissement dans les réseaux électriques: Luce Brotcorne - Reviewer
• Alyssia Dong, PhD, Ecole Normale Supérieure de Rennes, Algorithmes asynchrones pour la gestion décentralisée des réseaux électriques soumis aux aléas de communication: Luce Brotcorne - Member
• Andrea Di Placido, PhD, Universitá degli Studi del Molise, Italy, The Close Enough Traveling Salesman Problem: enhanced heuristics, applications and variants: Diego Cattaruzza - Member
• Gauthier Soleilhac, PhD, École Nationale Supérieure Mines-Télécom Atlantique Bretagne Pays-de-la-Loire - IMT Atlantique, Optimisation de la distribution de marchandises avec soustraitance du transport : une problématique chargeur: Diego Cattaruzza - Member
• Mahmoud Parham, PhD, University of Vienna, Austria, Algorithms for Traffic Control Challenges in Softwarized Networks: Bernard Fortz - Reviewer
• Nicola Morandi, PhD, KU Leuven, Belgium,Routing problems with node prizes and truck-drones synchronization: Bernard Fortz - Member
• Christian Biefel, PhD, Friedrich-Alexander-Universität Erlangen-Nürnberg, Contributions to Robust Optimization: Network Flows, Market Equilibria, Linear Complementarity Problems, and Pareto Optimality: Martine Labbé, reviewer.
• Niels Govaerts, PhD, KU Leuven, Distribution grid tariffs for active consumers, Hélène Le Cadre : reviewer
• Alexandre Borges de Jesus, PhD, University of Coimbra, Portugal, Algorithm selection for multi-objective optimization: Frédéric Semet – Member.

11.3.1 Internal Inria responsibilities

• Présidente de la commission CDT, Inria Lille: Luce Brotcorne.
• Membre élue de la commission d'évaluation Inria: Luce Brotcorne.

11.3.2 Education

• "Filles, maths et informatique : une équation lumineuse", Dunkerque , octobre 2022, Tifaout Almeftah.
• "Rendez-vous des Jeunes Mathématiciennes et Informaticiennes (RJMI)", Lille ,novembre 2022, Tifaout Almeftah.

International journals

• 11 articleJ.Javier Alcaraz, M.Martine Labbé and M.Mercedes Landete. Support Vector Machine with feature selection: A multiobjective approach.Expert Systems with Applications204May 2022, 117485
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• 12 articleS.Simon Belieres, M.Mike Hewitt, N.Nicolas Jozefowiez and F.Frédéric Semet. Meta Partial Benders Decomposition for the Logistics Service Network Design Problem.European Journal of Operational Research3002July 2022, 473-489
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• 13 articleJ.Jérôme de Boeck, L.Luce Brotcorne and B.Bernard Fortz. Strategic bidding in price coupled regions.Mathematical Methods of Operations Research952022, 365–407
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• 14 articleV.Víctor Bucarey, B.Bernard Fortz, N.Natividad González-Blanco, M.Martine Labbé and J. A.Juan A Mesa. Benders decomposition for Network Design Covering Problems.Computers and Operations Research2022
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• 15 articleM.Mandar Datar, E.Eitan Altman and H.Hélène Le Cadre. Strategic Resource Pricing and Allocation in a 5G Network Slicing Stackelberg Game.IEEE Transactions on Network and Service Management2022
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• 16 articleS.Sebastián Dávila, M.Martine Labbé, V.Vladimir Marianov, F.Fernando Ordóñez and F.Frédéric Semet. Product line optimization with multiples sites.Computers and Operations Research148105978December 2022
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• 17 articleB.Bernard Fortz, L.Luis Gouveia and P.Pedro Moura. A comparison of node‐based and arc‐based hop‐indexed formulations for the Steiner tree problem with hop constraints.Networks802September 2022, 178-192
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• 18 articleW.Wenjuan Gu, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier, F.Frédéric Semet and M. G.M Grazia Speranza. A sequential approach for a multi-commodity two-echelon distribution problem.Computers & Industrial Engineering163January 2022, 107793
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• 19 articleA.Arnaud Laurent, L.Luce Brotcorne and B.Bernard Fortz. Transaction fees optimization in the Ethereum blockchain.Blockchain: Research and Applications33September 2022, 100074
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• 20 articleS.Stefano Nasini, M.Martine Labbé and L.Luce Brotcorne. Multi-market portfolio optimization with conditional value at risk.European Journal of Operational Research3001November 2022, 350-365
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• 21 articleF.Fränk Plein, J.Johannes Thürauf, M.Martine Labbé and M.Martin Schmidt. A Bilevel Optimization Approach to Decide the Feasibility of Bookings in the European Gas Market.Mathematical Methods of Operations Research9532022, 409-449
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• 22 articleA.Anubhav Ratha, P.Pierre Pinson, H.Hélène Le Cadre, A.Ana Virag and J.Jalal Kazempour. Moving from Linear to Conic Markets for Electricity.European Journal of Operational Research2022
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• 23 articleA.Anibal Sanjab, H.Hélène Le Cadre and Y.Yuting Mou. TSO-DSOs Stable Cost Allocation for the Joint Procurement of Flexibility: A Cooperative Game Approach.IEEE Transactions on Smart Grid2022
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International peer-reviewed conferences

• 24 inproceedingsL.Luce Brotcorne, B.Bruno Francois and H.Haider Ali. Optimal siting and sizing of charging stations for autonomous electric vehicle fleet with local renewable energy generation.CIRED Porto Workshop 2022: E-mobility and power distribution systemsPorto, Portugal2022
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• 25 inproceedingsC.Clément Legrand, D.Diego Cattaruzza, L.Laetitia Jourdan and M.-E.Marie-Eléonore Kessaci. Machine Learning for Multi-Objective Problems.23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la DécisionVilleurbanne - Lyon, FranceFebruary 2022
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• 26 inproceedingsA.Aitor López Sánchez, M.Marin Lujak, F.Frederic Semet and H.Holger Billhardt. On balancing fairness and efficiency in routing of cooperative vehicle fleets.Twelfth International Workshop on Agents in Traffic and Transportation co-located with the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022)3173ATT 2022 Agents in Traffic and TransportationVienne, AustriaJuly 2022
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• 27 inproceedingsT.Thibault Prunet, N.Nabil Absi, V.Valeria Borodin and D.Diego Cattaruzza. Branch-Cut-and-Price algorithm for an Operational Storage Location Assignment Problem.23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la DécisionVilleurbanne - Lyon, FranceFebruary 2022
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• 28 inproceedingsI.Ilia Shilov, H.Hélène Le Cadre and A.Ana Bušić. A Generalized Nash Equilibrium analysis of the interaction between a peer-to-peer financial market and the distribution grid.ROADEF 2022 - 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la DécisionVilleurbanne - Lyon, FranceFebruary 2022
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National peer-reviewed Conferences

• 29 inproceedingsA.Arnaud Laurent, L.Luce Brotcorne and B.Bernard Fortz. Modèle bi-niveau pour la tarification de ressources de cloud computing.ROADEF 2022 - 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la DécisionVilleurbanne - Lyon, FranceFebruary 2022
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• 30 inproceedingsM.Matteo Petris, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier and F.Frederic Semet. A branch-price-and-cut approach for the Multi-Commodity two-echelon Distribution Problem.23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la DécisionVilleurbanne - Lyon, FranceFebruary 2022
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• 31 inproceedingsP.Pablo Torrealba-González, D.Dominique Feillet, M.Maxime Ogier and F.Frederic Semet. Joint Order Batching and Picker Routing Problem including congestion.23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la DécisionVilleurbanne - Lyon, FranceFebruary 2022
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Conferences without proceedings

• 32 inproceedingsO.Olivier Briant, H.Hadrien Cambazard, D.Diego Cattaruzza, N.Nicolas Catusse, A.-L.Anne-Laure Ladier and M.Maxime Ogier. A bin-packing formulation for the joint order batching, picker routing and picker sequencing problem.EURO 2022Espoo, FinlandJuly 2022
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• 33 inproceedingsL.Luce Brotcorne, B.Bernard Fortz and L.Laurent Arnaud. New cloud computing resources pricing strategies.EuroEspoo, FinlandJuly 2022
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• 34 inproceedingsL.Luce Brotcorne. How to integrate and influence customer’s behaviour within pricing:A bilevel optimization approach.French German Portuguese conference on OptimizationPorto, PortugalMay 2022
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• 35 inproceedingsL.Luce Brotcorne, H.Hélène Le Cadre and J.Juan Sepúlveda. A Reverse Stackelberg Game Model for Grid Usage Pricing.informsIndianapolis, United StatesOctober 2022
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• 36 inproceedingsC.Clément Legrand, D.Diego Cattaruzza, L.Laetitia Jourdan and M.-E.Marie-Eléonore Kessaci. Enhancing MOEA/D with Learning: Application to Routing Problems with Time Windows.GECCO '22: Genetic and Evolutionary Computation ConferenceBoston, United StatesJuly 2022
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• 37 inproceedingsM.Matteo Petris, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier and F.Frédéric Semet. A Matheuristic for the Commodity Constrained Split Delivery VRP.ROUTE 2022, International workshop on vehicle routing and logisticsSnekkersten, DenmarkMay 2022
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• 38 inproceedingsM.Matteo Petris, C.Claudia Archetti, D.D Cattaruzza, M.Maxime Ogier and F.Frédéric Semet. A branch-price-and-cut algorithm for a multi-commodity two-echelon distribution problem.Triennal Symposium on Transportation Analysis - TRISTAN XIBalaclava, MauritiusJune 2022
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• 39 inproceedingsM.Matteo Petris, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier and F.Frédéric Semet. A branch-price-and-cut algorithm for the Multi-Commodity two-echelon Distribution Problem.Odysseus 2021: the eight international workshop on freight transportation and logisticsTangier, MoroccoMay 2022
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• 40 inproceedingsM.Matteo Petris, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier and F.Frédéric Semet. An exact algorithm for the Multi-Commodity two-echelon Distribution Problem.VeRoLog 2022: 8th meeting of the EURO Working Group on Vehicle Routing and Logistics Optimization (VeRoLog)Hamburg, GermanyJune 2022
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• 41 inproceedingsT.Thibault Prunet, N.Nabil Absi, V.Valeria Borodin and D.D Cattaruzza. Branch-Cut-and-Price Algorithm for an Integrated Storage Location Assignment and Picker Routing Problem.Odysseus 2021Tanger, MoroccoMay 2022
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• 42 inproceedingsP.Pablo Torrealba-González, D.Dominique Feillet, M.Maxime Ogier and F.Frédéric Semet. Joint Order Batching and Picker Routing Problem including congestion.VeRoLog 2022 - Workshop of the EURO Working Group on Vehicle Routing and Logistics optimizationHamburg, GermanyJune 2022
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• 43 inproceedingsP.Pablo Torrealba-González, D.Dominique Feillet, M.Maxime Ogier and F.Frédéric Semet. Joint Order Batching and Picker Routing Problem including congestion.ORBEL 36Gent, BelgiumSeptember 2022
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Reports & preprints

• 44 miscY.Yasemin Arda, D.Diego Cattaruzza, V.Véronique François and M.Maxime Ogier. Home Chemotherapy Planning: An Integrated Production Scheduling and Multi-Trip Vehicle Routing Problem.July 2022
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• 45 miscE.Eric Bourreau, B.Bernard Fortz, A.Amaury Pachurka, M.Michael Poss and M.Mariam Sangaré. Loads scheduling for demand response in energy communities.December 2022
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• 46 miscD.Diego Cattaruzza, M.Martine Labbé, M.Matteo Petris, M.Marius Roland and M.Martin Schmidt. Exact and Heuristic Solution Techniques for Mixed-Integer Quantile Minimization Problems.May 2022
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• 47 miscC.Christian Clavijo López, Y.Yves Crama, T.Thierry Pironet and F.Frédéric Semet. Multi-period distribution networks with purchase commitment contracts.2022
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• 48 miscM.Mandar Datar, E.Eitan Altman and H.Hélène Le Cadre. Strategic Resource Pricing and Allocation in a 5G Network Slicing Stackelberg Game.November 2022
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• 49 miscM.Matteo Petris, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier and F.Frédéric Semet. A heuristic with a performance guarantee for the Commodity constrained Split Delivery Vehicle Routing Problem.January 2023
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• 50 miscT.Thibault Prunet, N.Nabil Absi, V.Valeria Borodin and D.Diego Cattaruzza. Optimization of Human-Aware Manufacturing and Logistics Systems: A Comprehensive Review of Modeling Approaches and Applications.September 2022
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• 51 miscT.Thibault Prunet, N.Nabil Absi, V.Valeria Borodin and D.Diego Cattaruzza. Optimization of Human-Aware Manufacturing and Logistics Systems: A Survey on the Modeling Frameworks of Human Aspects.September 2022
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• 52 miscI.Ilia Shilov, H.Hélène Le Cadre, A.Ana Bušić and G.Gonçalo de Almeida Terça. A Stackelberg Game Analysis of Risk-Hedging Strategies in Decentralized Electricity Markets.January 2023
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• 53 miscZ.Zeynep Şuvak, M. F.Miguel F Anjos, L.Luce Brotcorne and D.Diego Cattaruzza. Design of Poisoning Attacks on Linear Regression Using Bilevel Optimization.January 2022
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• 54 miscR.Raphaël Taisant, M.Mandar Datar, H.Hélène Le Cadre and E.Eitan Altman. Balancing Efficiency and Privacy in a Decision-Dependent Network Game.October 2022
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Other scientific publications

• 55 miscM.Matteo Petris, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier and F.Frédéric Semet. Instances and detailed results for the whole testbed of "A Branch-Price-and-Cut algorithm for the Multi-Commodity two-echelon Distribution Problem".January 2023
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• 56 miscM.Matteo Petris, C.Claudia Archetti, D.Diego Cattaruzza, M.Maxime Ogier and F.Frédéric Semet. Instances and detailed results for the whole testbed of "A heuristic with a performance guarantee for the Commodity constrained Split Delivery Vehicle Routing Problem".November 2022
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• 57 miscR.Raphaël Taisant, M.Mandar Datar, H.Hélène Le Cadre and E.Eitan Altman. Balancing Efficiency and Privacy in a Decision-Dependent Network Game.Palaiseau, FranceNovember 2022
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