Pareto Front Computation
Pareto Front Computation is a method in multi-objective Markov decision processes that identifies the set of non-dominated policies by simultaneously optimizing multiple conflicting objectives, where no alternative policy can improve one objective without degrading another.
443
Publications
23.6K
Citations
1.3K
Authors
567
Institutions
Publications per year
2017–2026
171
443
Himanshu Jain, Kalyanmoy Deb · IEEE Transactions on Evolutionary Computation · 2013 · 2.1K citations
1–5 of 443
1.3K
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Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico
6 publications · 763 citations
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1–5 of 1.3K
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Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional
Mexico City, Mexico
9 h-index
18 publications
1.9K citations

Centre National de la Recherche Scientifique
Paris, France
9 h-index
13 publications
472 citations

City University of Hong Kong
Hong Kong, Hong Kong
8 h-index
17 publications
1K citations
Texas A&M University
College Station, United States
7 h-index
15 publications
490 citations
TU Dortmund University
Dortmund, Germany
6 h-index
7 publications
468 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
15 publications
546 citations
Politecnico di Milano
Milan, Italy
6 h-index
17 publications
1.1K citations

Instituto Politécnico Nacional
Mexico City, Mexico
6 h-index
15 publications
1.8K citations
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11 publications · 3.9K citations
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Repository · 10 publications · 193 citations
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9 publications · 388 citations
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8 publications · 608 citations
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7 publications · 973 citations
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