Multiobjective Genetic Algorithms
Multiobjective Genetic Algorithms is a computational optimization framework within evolutionary computation that extends genetic algorithms to simultaneously optimize multiple conflicting objectives by maintaining a population of solutions and using mechanisms such as nondominated sorting and diversity preservation to converge toward a Pareto-optimal front.
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2017–2026
437
Variants
MogaMulti-objective Genetic Algorithms
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A niched Pareto genetic algorithm for multiobjective optimization
Jeffrey Horn, N. Nafpliotis, David E. Goldberg · 2002 · 2.4K citations
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Indian Institute of Technology Kharagpur
Kharagpur, India
24 h-index
79 publications
3.4K citations
University of Sheffield
Sheffield, United Kingdom
24 h-index
81 publications
4.4K citations
University of Illinois Urbana-Champaign
Urbana, United States
21 h-index
59 publications
11K citations

Indian Institute of Technology Kanpur
Kanpur, India
18 h-index
38 publications
208K citations
National University of Singapore
Singapore, Singapore
18 h-index
50 publications
2.9K citations

Indian Statistical Institute
Kolkata, India
17 h-index
24 publications
2.5K citations

Centre National de la Recherche Scientifique
Paris, France
17 h-index
62 publications
2.2K citations

Huazhong University of Science and Technology
Wuhan, China
17 h-index
52 publications
3.6K citations
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