A Machine-Learning Approach to Select Important Variables for Recombination on Many-objective Evolutionary Optimization | Zendy

Miyako Sagawa | Zendy; Hernán Aguirre | Zendy; Fabio Daolio | Zendy; Arnaud Liefooghe | Zendy; Bilel Derbel | Zendy; Sebástien Vérel | Zendy; Kiyoshi Tanaka | Zendy

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A Machine-Learning Approach to Select Important Variables for Recombination on Many-objective Evolutionary Optimization

Author(s) -

Miyako Sagawa,

Hernán Aguirre,

Fabio Daolio,

Arnaud Liefooghe,

Bilel Derbel,

Sebástien Vérel,

Kiyoshi Tanaka

Publication year - 2018

Publication title -

international journal of smart computing and artificial intelligence

Language(s) - English

Resource type - Journals

eISSN - 2185-9914

pISSN - 2185-9906

DOI - 10.52731/ijscai.v2.i1.285

Subject(s) - benchmark (surveying) , evolutionary algorithm , computer science , multi objective optimization , variation (astronomy) , variable (mathematics) , convergence (economics) , mathematical optimization , ranking (information retrieval) , selection (genetic algorithm) , pareto principle , optimization problem , artificial intelligence , machine learning , mathematics , geography , geodesy , physics , astrophysics , economics , mathematical analysis , economic growth

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