Arnaud Liefooghe
researcher ORCID ID = 0000-0003-3283-3122
Facts
9 properties- Instance of
- human
- Date of birth
- 1982
- Occupation
- researcher, computer scientist
- Official website
- cristal.univ-lille.fr[9]
- Doctoral advisor
- El-Ghazali Talbi, Laetitia Jourdan[5][6]
- Maintained by WikiProject
- WikiProject Mathematics[10]
🏷️ Also known as
en Arnaud Liefooghe
🔖 Identifiers · 14
- ISNI
- 0000000359681755
- ORCID iD
- 0000-0003-3283-3122
- VIAF cluster ID
- 220381366
- GND ID
- 1021997951
- DBLP author ID
- 90/304
- Dimensions author ID
- 012326273133.34
- Google Knowledge Graph ID
- /g/11f0ytsmt0
- Google Scholar author ID
- Y2kuG1sAAAAJ
- HAL author ID
- arnaud-liefooghe
- IdRef ID
- 144113910
- National Library of Israel J9U ID
- 987007403874305171
- Scopus author ID
- 23091255000
Show all 14 identifiers +2
- Yale LUX ID
- person/16a0062b-4f2b-4f8e-93a1-813b57c57d72
- ZbMATH author ID
- liefooghe.arnaud
🔗 Connections
Affiliated with 9
University of Tokyo,
National Center for Scientific Research,
École Centrale de Lille,
University of Lille,
International Research Center for Japanese Studies,
Centre de Recherche en Informatique,
Centre de Recherche en Informatique, Signal et Automatique de Lille,
Inria research centre Lille - Nord Europe
+1 more
Author of 8
A fine-grained message passing MOEA/D,
Algorithm selection of anytime algorithms,
Experiments on Greedy and Local Search Heuristics for <i>d</i> dimensional Hypervolume Subset Selection,
Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems,
Paradiseo: from a modular framework for evolutionary computation to the automated design of metaheuristics,
Pareto Local Optimal Solutions Networks with Compression, Enhanced Visualization and Expressiveness,
Surrogate assisted evolutionary algorithm for medium scale multi-objective optimisation problems,
What if we increase the number of objectives? Theoretical and empirical implications for many-objective combinatorial optimization
← Authored by 8
A fine-grained message passing MOEA/D,
Algorithm selection of anytime algorithms,
Experiments on Greedy and Local Search Heuristics for <i>d</i> dimensional Hypervolume Subset Selection,
Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems,
Paradiseo: from a modular framework for evolutionary computation to the automated design of metaheuristics,
Pareto Local Optimal Solutions Networks with Compression, Enhanced Visualization and Expressiveness,
Surrogate assisted evolutionary algorithm for medium scale multi-objective optimisation problems,
What if we increase the number of objectives? Theoretical and empirical implications for many-objective combinatorial optimization
Press Enter · cited answer in seconds