Présentation
Le Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS) est une Unité Mixte de Recherche (UMR 6158) en informatique, et plus généralement en Sciences et Technologies de l'Information et de la Communication (STIC).
(lire la suite)Dernières Publications
Tapas Das, Florent Foucaud, Clara Marcille, P.D. Pavan, Sagnik Sen - 21 mars 2025
Monitoring arc-geodetic sets of oriented graphs
Theoretical Computer Science
Ahmad Hashemi, Hamed Gholami, Xavier Delorme, Kuan Yew Wong - 1 avril 2025
A multidimensional fitness function based heuristic algorithm for set covering problems
Applied Soft Computing
Diego Perdigão Martino, Philippe Lacomme, Katyanne Farias - 1 juin 2025
A split-embedded metaheuristic for the heterogenous inventory routing problem with batch size
European Journal of Operational Research
Benjamin Bergougnoux, Vera Chekan, Robert Ganian, Mamadou Moustapha Kanté, Matthias Mnich, Sang-Il Oum, Michal Pilipczuk, Erik Leeuwen - 18 mars 2025
Space-Efficient Parameterized Algorithms on Graphs of Low Shrubdepth
ACM Transactions on Computation Theory
Anis Fradi, Tien-Tam Tran, Chafik Samir - 7 avril 2025
Decomposed Gaussian Processes for Efficient Regression Models with Low Complexity
Entropy
Monitoring arc-geodetic sets of oriented graphs
Theoretical Computer Science
Ahmad Hashemi, Hamed Gholami, Xavier Delorme, Kuan Yew Wong - 1 avril 2025
A multidimensional fitness function based heuristic algorithm for set covering problems
Applied Soft Computing
Diego Perdigão Martino, Philippe Lacomme, Katyanne Farias - 1 juin 2025
A split-embedded metaheuristic for the heterogenous inventory routing problem with batch size
European Journal of Operational Research
Benjamin Bergougnoux, Vera Chekan, Robert Ganian, Mamadou Moustapha Kanté, Matthias Mnich, Sang-Il Oum, Michal Pilipczuk, Erik Leeuwen - 18 mars 2025
Space-Efficient Parameterized Algorithms on Graphs of Low Shrubdepth
ACM Transactions on Computation Theory
Anis Fradi, Tien-Tam Tran, Chafik Samir - 7 avril 2025
Decomposed Gaussian Processes for Efficient Regression Models with Low Complexity
Entropy