+30 ans d'expertise
Notre expérience scientifique
Avec 30 ans d’expérience académique Atoptima est reconnue pour ses logiciels basés sur son expertise scientifique et ses partenariats académiques continus. Spin-off d’une équipe conjointe Inria / CNRS de l’Université de Bordeaux, les experts d’Atoptima industrialisent des technologies de pointe afin de développer des logiciels d’optimisation disruptifs. Atoptima rassemble une équipe d’experts dotés de hautes qualifications et d’un fort potentiel de R&D. Avec des thèses industrielles et des chercheurs qui contribuent quotidiennement au développement de sa librairie logicielle, des articles pionniers continuent d’être publiés dans les grandes revues et conférences internationales.
Découvrir AtoptimaColuna, notre plateforme Open-Source
Coluna est un framework de “branch-and-price-and-cut” écrit en Julia. L’utilisateur présente un MIP original qui modélise son problème à l’aide du langage de modélisation JuMP et de notre extension spécifique BlockDecomposition qui propose une syntaxe pour spécifier la décomposition du problème. Ensuite, Coluna reformule le MIP d’origine et optimise la reformulation à l’aide des algorithmes choisis par l’utilisateur. Coluna vise à être très modulaire et modifiable afin que tout utilisateur puisse définir le comportement de son algorithme personnalisé de “branch-and-price-and-cut”.
Quelques articles scientifiques publiés par notre équipe R&D
Exact Approaches for Single Machine Total Weighted Tardiness Batch Scheduling
INFORMS Journal on Computing, 2022
Branch-and-cut-and-price for the robust capacitated vehicle routing problem with knapsack uncertainty
Operations Research, INFORMS, 2021, 69 (3), pp.739-754. ⟨10.1287/opre.2020.2035⟩
BaPCod - a generic branch-and-price code
[Technical Report] Inria Bordeaux Sud-Ouest. 2021
Combining Dantzig-Wolfe and Benders decompositions to solve a large-scale Nuclear Outage Planning Problem.
European Journal of Operational Research. July 2021
A Bucket Graph Based Labelling Algorithm for Vehicle Routing
Transportation Science, INFORMS, 2020, Ahead of Print, ⟨10.1287/trsc.2020.0985⟩
Solving Bin Packing Problems Using VRPSolver Models
SN Operations Research Forum, Springer, In press
A Generic Exact Solver for Vehicle Routing and Related Problems
Mathematical Programming, Springer Verlag, 2020, 183, pp.483-523. ⟨10.1007/s10107-020-01523-z⟩
An improved branch-cut-and-price algorithm for the two-echelon capacitated vehicle routing problem
Computers and Operations Research, Elsevier, 2020, 114, pp.104833. ⟨10.1016/j.cor.2019.104833⟩
On the exact solution of a large class of parallel machine scheduling problems
Journal of Scheduling, Springer Verlag, 2020, 23, pp.411-429. ⟨10.1007/s10951-020-00640-z⟩
On the exact solution of vehicle routing problems with backhauls
European Journal of Operational Research, Elsevier, 2020, 287 (1), pp.76-89. ⟨10.1016/j.ejor.2020.04.047⟩
Two-echelon vehicle routing problems in city logistics : approaches based on exact methods of mathematical optimization
Operations Research [cs.RO]. Université de Bordeaux, 2020. English
Pattern based diving heuristics for a two-dimensional guillotine cutting-stock problem with leftovers
EURO Journal on Computational Optimization, Springer, 2019, 7 (3), pp.265-297. ⟨10.1007/s13675-019-00113-9⟩
Designing a Two-Echelon Distribution Network under Demand Uncertainty
European Journal of Operational Research, Elsevier, In press, 280 (1), pp.102-123. ⟨10.1016/j.ejor.2019.06.047⟩
Primal Heuristics for Branch-and-Price: the assets of diving methods
INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS), 2019, 31 (2), pp.251-267. ⟨10.1287/ijoc.2018.0822⟩
Bandwidth-optimal Failure Recovery Scheme for Robust Programmable Networks
[Research Report] INRIA Sophia Antipolis - I3S. 2019
Combining dynamic programming with filtering to solve a four-stage two-dimensional guillotine-cut bounded knapsack problem
Discrete Optimization, Elsevier, 2018, 29, pp.18-44. ⟨10.1016/j.disopt.2018.02.003⟩
Automation and combination of linear-programming based stabilization techniques in column generation
INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS), 2018, 30 (2), pp.339-360. ⟨10.1287/ijoc.2017.0784⟩
Stochastic Two-echelon Location-Routing
ISMP 2018 - 23rd International Symposium on Mathematical Programming, Jul 2018, Bordeaux, France
Reformulation and Decomposition Approaches for Traffic Routing in Optical Networks
Networks, Wiley, 2016, 67 (4), pp.277-298
Designing Two-Echelon Distribution Network under Demand Uncertainty
VEROLOG, Jun 2016, Nantes, France
A Column Generation Based Heuristic for the Dial-A-Ride Problem
International Conference on Information Systems, Logistics and Supply Chain (ILS), Jun 2016, Bordeaux, France
A column generation approaches for the software clustering problem
Computational Optimization and Applications, Springer Verlag, 2015, ⟨10.1007/s10589-015-9822-9⟩
Column Generation for Extended Formulations
EURO Journal on Computational Optimization, Springer, 2013, 1 (1-2), pp.81-115. ⟨10.1007/s13675-013-0009-9⟩
Bin Packing with conflicts: a generic branch-and-price algorithm
INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS),2013, 25 (2), pp.244-255. ⟨10.1287/ijoc.1120.0499⟩
A Column Generation based Tactical Planning Method for Inventory Routing
Operations Research, INFORMS, 2012, Operations Research, 60 (2), pp.382-397
Branching in Branch-and-Price: a Generic Scheme
Mathematical Programming, Series A, Springer, 2011, 130, pp.249-294. ⟨10.1007/s10107-009-0334-1⟩
Reformulation and Decomposition of Integer Programs
Jünger, M. and Liebling, Th.M. and Naddef, D. and Nemhauser, G.L. and Pulleyblank, W.R. and Reinelt, G. and Rinaldi, G. and Wolsey, L.A. 50 Years of Integer Programming 1958-2008, Springer, 2010, ⟨10.1007/978-3-540-68279-0_13⟩
Knapsack Problems with Setups
European Journal of Operational Research, Elsevier, 2009, 196, pp.909-918
Comparison of Bundle and Classical Column Generation
Mathematical Programming, Springer Verlag, 2008, 113 (2), pp.299-344. ⟨10.1007/s10107-006-0079-z⟩
Column generation based heuristic for tactical planning in multi-period vehicle routing
European Journal of Operational Research, Elsevier, 2007, 183 (3), pp.1028-1041. ⟨10.1016/j.ejor.2006.02.030⟩
A generic view of Dantzig–Wolfe decomposition in mixed integer programming
Operations Research Letters, Elsevier, 2006, 34 (3), pp.296-306. ⟨10.1016/j.orl.2005.05.009⟩
Periodic Vehicle Routing Problem: classification and heuristic -- Problème de tournées de véhicules multipériodiques : classification et heuristique pour la planification tactique
RAIRO - Operations Research, EDP Sciences, 2006, 40, pp.169-194. ⟨10.1051/ro:2006015⟩
Implementing Mixed Integer Column Generation
G. Desaulniers, J. Desrosiers, and M.M. Solomon. Column Generation, Springer, 2005, Kluwer's series in Operation Research
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