2/20/2023 0 Comments Hemera lille![]() ![]() ( M aster student projects) algorithm selection | global meta-model assisted optim. (Open Fundings) We are seeking for good and motivated candidates for internships, master / PhD thesis, post-docs. ![]() (Past Event) The new IEEE CIS Task Force on Decomposition-based Techniques in Evolutionary Computation and subscribe to the MOEA/D mailing list ! (Past Event) The new MOEA/D website including multi-objective decomposition related resources is up. (Past Event) 2nd Special session on " Advances in Decomposition-based Evolutionary Multi-objective Optimization (ADEMO) ", WCCI/CEC 2018 (Rio, Brazil) | deadline: Feb 1, 2018 (Past Event) Special session on " Multi-/many-objective optimization and learning ", BIOMA 2018 (Paris, France) | deadline: Dec 1, 2018 ( Past Event ) 1st GECCO workshop on " Decomposition Techniques in Evolutionary Optimization ", DTEO GECCO 2018 (Kyoto, Japan) | deadline extended: April 03, 2018 (Past Event) 3rd Special session on " Advances in Decomposition-based Evolutionary Multi-objective Optimization (ADEMO) ", CEC 2019 (Wellington, New Zealand) | deadline: Jan 7, 2019 ( Past Event ) 2nd GECCO workshop on " Decomposition Techniques in Evolutionary Optimization ", DTEO GECCO 2019 (Kyoto, Japan) | deadline extended: April 03, 2018 (Pas t Event ) 3rd GECCO workshop on " Decomposition Techniques in Evolutionary Optimization ", DTEO GECCO 2020 (Cancun, Mexico) | deadline extended: April 17, 2020 (Event) 6th Special session on " Advances in Decomposition-based Evolutionary Multi-objective Optimization (ADEMO) ", WCCI 2022 ( Padua, Italy ) | deadline: Feb 14, 20 22 ( Event ) 5th GECCO workshop on " Decomposition Techniques in Evolutionary Optimization ", DTEO GECCO 202 2 ( Boston, USA ) | deadline : April 1 1, 202 2 Surrogate-based algorithms), Parallel multi-objective search algorithms Multiobjective Optimization : Decomposition based algorithms (e.g., MOEA/D), Meta-model based expensive optimization (e.g. Parallel and Distributed Computing : Locality and graph based algorithms, Cluster and grid computing, Parallel Branch and Bound ![]() High Level Optimization Techniques : Randomized search heuristics (e.g., evolutionary algorithms, local search), fitness landscape analysis, c ross-domain and autonomous optimization (e.g., tuning, adaptation, control), Combinatorial optimization (e.g., 0/1 problems, permutation problem s ), Machine learning and optimization (e.g., auto-ML, multi-armed bandits, tree search, etc) His current research topics are on the design and analysis of algorithms for solving complex and large scale optimization problems with a particular focus on: He did his Ph.D at the University of Bordeaux, LaBRI Laboratory. He is a co-founder member of the MODŌ International Associated Laboratory (LAI) between the University of Lille and Shinshu University, Nagano, Japan. He is a Collaborative Professor at Shinshu University, Japan. He is deputy team leader of BONUS, a joint research group at the CRIStAL Laboratory and the Inria Lille Nord Europe research center. It does not store any personal data.Bilel Derbel is an associate P rofessor (HDR - Research Habilitation) at the Computer Science Department of the University of Lille. The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. The cookie is used to store the user consent for the cookies in the category "Performance". This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". The cookie is used to store the user consent for the cookies in the category "Other. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". The cookie is used to store the user consent for the cookies in the category "Analytics". These cookies ensure basic functionalities and security features of the website, anonymously. Necessary cookies are absolutely essential for the website to function properly. ![]()
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