Liens
Articles de conférence
January 2023 Walsh-based surrogate-assisted multi-objective combinatorial optimization: A fine-grained analysis for pseudo-boolean functions
Bilel Derbel, Geoffrey Pruvost, Arnaud Liefooghe, Sébastien Verel, Qingfu Zhang
Journal of Applied Soft Computing PDF
October 2022 Moead-framework: a modular MOEA/D Python framework
Geoffrey Pruvost, Bilel Derbel, Arnaud Liefooghe
Journal of Open Source Software PDF
June 2021 Enhancing MOEA/D with Escape Mechanisms
Bilel Derbel, Geoffrey Pruvost, Byung-Woo Hong
IEEE Congress on Evolutionary Computation (IEEE CEC 2021) PDF - Cite the paper [BIB File]
July 2020 Surrogate-assisted Multi-objective Combinatorial Optimization based on Decomposition and Walsh Basis
Geoffrey Pruvost, Bilel Derbel, Arnaud Liefooghe, Sébastien Verel, Qingfu Zhang
Genetic and Evolutionary Computation Conference (GECCO 2020) [PDF] - [slides] - Video - [Cite the paper [BIB File]]
April 2020 On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D
Geoffrey Pruvost, Bilel Derbel, Arnaud Liefooghe, Ke Li, Qingfu Zhang
Evolutionary Computation in Combinatorial Optimization. EvoCOP 2020. Lecture Notes in Computer Science, vol 12102. Springer, Cham [PDF] - [slides] - Video - [Cite the paper [BIB File]]
Thèse
2018 - 2021 University of Lille / Inria Machine Learning and Decomposition Techniques for Large-scale Multi-objective Optimization