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Awards
Prix Robert Faure , first prize, 2022. Awarded every three years to a researcher under 35 years of age by the French Society of Operations Research.
PhD award, AMIES 2017, best PhD in applied mathematics for the industry by the French agency for mathematics related to industry and society (AMIES).
Young researcher award, ROADEF 2016, first prize.
Awards won by students for projects done under my supervision
Leo Baty won the EURO NeurIPS VRP challenge 2022
Louis Bouvier won the Prix Master RO/AD 2022 of the ROADEF
Julie Poullet won the Prix du stage de recherche de la fondation de l'X 2018
Preprints and articles in journals
Jungel, K., Parmentier, A., Schiffer, M., Vidal, T. (2023) Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet Control. arXiv preprint arXic:2302.03963.
Forel, A., Parmentier, A., Vidal. T. (2023) Explainable Data-Driven Optimization: From Context to Decision and Back Again. arXiv preprint arXiv:2301.10074.
Bouvier, L., Dalle, G., Parmentier, A., Vidal, T. (2022) Solving a Continent-Scale Inventory Routing Problem at Renault. arXiv preprint arXiv:2209.00412.
Dalle, G., Baty, L., Bouvier, L., Parmentier, A. (2022) Learning with Combinatorial Optimization Layers: a Probabilistic Approach. arXiv preprint arXiv:2207.13513.
Forel, A., Parmentier, A., Vidal, T. (2022) Robust Counterfactual Explanations for Random Forests. arXiv preprint arXiv:2205.14116.
Tellache, N.E., Meunier, F., Parmentier, A. (2022), Linear lexicographic optimization and preferential bidding system. arXiv preprint arXiv:2201.08907.
Parmentier, A. (2021) Learning structured approximations of operations research problems. HAL preprint hal-03281894
Parmentier, A., Martinelli, R., Vidal, T. (2021) Mobility-on-Demand with Electric Vehicles: Scalable Route and Recharging Planning through Column Generation. (Accepted in Transportation Science (2023)), arXiv preprint arXiv:2104.03823.
Parmentier, A., & T'Kindt, V. (2021) Learning to solve the single machine scheduling problem with release times and sum of completion times. arXiv preprint arXiv:2101.01082. (Accepted in European Journal of Operational Research)
Cohen, V., & Parmentier, A. (2020) Integer Programing for Weakly Coupled Stochastic Dynamic Programs with Partial Information. arXiv preprint arXiv:2012.00645.
Parmentier, A. (2020). Learning to approximate industrial problems by operations research classic problems. Operations Research. Preprint. Talk.
Parmentier, A., Cohen, V., Leclere, V., Obozinski, G., & Salmon, J. (2020). Integer programming on the junction tree polytope for influence diagrams. Informs Journal on Optimization, 2(3), 209-228. Preprint
Poullet, J., & Parmentier, A. (2020). Shift Planning Under Delay Uncertainty at Air France: A Vehicle-Scheduling Problem with Outsourcing. Transportation Science. Preprint
Cohen, V., & Parmentier, A. (2019). Two generalizations of Markov blankets. arXiv preprint arXiv:1903.03538.
Parmentier, A., & Meunier, F. (2019). Aircraft routing and crew pairing: updated algorithms at air France. Omega.
Cohen, V., & Parmentier, A. (2018). Linear Programming for Decision Processes with Partial Information. arXiv preprint arXiv:1811.08880.
Kruber, M., Parmentier, A., & Benchimol, P. (2018). Resource constrained shortest path algorithm for EDF short-term thermal production planning problem. arXiv preprint arXiv:1809.00548 .
Parmentier, A. (2018). Algorithms for non-linear and stochastic resource constrained shortest paths. in Mathematical Methods of Operations Research
Parmentier, A., & Meunier, F. (2014). Stochastic shortest paths and risk measures. arXiv preprint arXiv :1408.0272.
Conferences with proceedings
Parmentier, A., Vidal, T. (2021) Optimal Counterfactual Explanations in Tree Ensembles. Accepted in the thirty-eighth International Conference on Machine Learning (ICML 2021). Preprint. Code.
Kruber, M., Luebbecke, M. E., & Parmentier, A. (2017, June). Learning when to use a decomposition. In CPAIOR 2017 International Conference on AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (pp. 202-210). Springer, Cham .
Parmentier, A., Samaranayake, S., Xuan, Y., & Bayen, A. (2015). A mathematical framework for delay analysis in single source networks. In American control conference 2015.
Samaranayake, S., Parmentier, A., Xuan, E., & Bayen, A. (2015). Solving the user equilibrium departure time problem at an off-ramp with incentive compatible cost functions solving the user equilibrium departure time problem at an off-ramp with incentive compatible cost functions. In European control conference 2015.
PhD dissertation
Algorithms for shortest path and airline problems
Research topics
Operations research and its applications, machine learning for operations research, data driven optimization, stochastic optimization, graph theory.