Combinatorial Optimization consists in finding a "best" choice among a finite (but usually very large) set of possibilities. We find and use structural properties of the problems we consider ("good" caracterizations, decompositions, ...) in order to design efficient algorithms (exact or approximate) or to show that such algorithms do not exist. [More...]
Staff
Research projects
- ANR ENEDISC (2024-2028), with LIRIS (Lyon), LaBRI (Bordeaux), and IRIF (Paris)
- ANR GRALMECO (2022-2025), with LIMOS (Clermont-Ferrand)
- ANR Twinwidth (2021-2025), with LIP (Lyon) and LAMSADE (Paris)
- ANR DAGDigDec (2021-2025), with LAMSADE, ENS and IRIF (Paris)
Recent PhD students
- Paul Colinot, supervised by Alantha Newman (2024-...)
- Pierre Hoppenot, supervised by Aurélie Lagoutte et Zoltàn Szigeti (2023-...)
- Benjamin Peyrille, supervised by Moritz Mühlenthaler and Zoltàn Szigeti (2022-...)
- Florent Tallerie,supervised by Françis Lazarus, defended in October 2024 :
Plongements isométriques PL de surfaces plates - Thomas Suzan, supervised by Louis Esperet and Moritz Mühlenthaler, defended in Septermber 2024 : Graphes solutions de problèmes combinatoires : algorithmes et complexité
- Ugo Giocanti, supervised by Louis Esperet et Stéphan Thomassé, defended in July 2024 : Propriétés structurelles et géométriques des graphes fortement symétriques
- Félix Klingelhoefer, supervised by Louis Esperet and Alantha Newamn, defended in December 2023 : Algorithmes pour des Problèmes de Coloration avec Promesse sur les Tournois et les Graphes
- Marco Caoduro, supervised by Andràs Sebő and Matěj Stehlík, defended in November 2022 : Problèmes de géométrie en optimisation combinatoire : packing, transversaux, et coloration de rectangles
For older thesis, please visit our page about Former Members.
