Coevolutionary Optimization is a computational optimization paradigm within evolutionary algorithms where solutions and performance evaluation criteria mutually adapt through iterative interaction, thereby driving concurrent improvement in both problem-solving strategies and fitness assessment mechanisms.
266
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13.9K
Citations
646
Authors
274
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Publications per year
2017–2026
79
Parents
Publications
266
1–5 of 266
Authors
646
- RP
8
h-index
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8
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7
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7
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6
h-index
1–5 of 646
Institutions
274
Xidian University
Xi'an, China
11 h-index
45 publications
2.7K citations
Xi'an Jiaotong University
Xi'an, China
10 h-index
33 publications
1K citations
George Mason University
Fairfax, United States
8 h-index
14 publications
565 citations
City University of Hong Kong
Hong Kong, Hong Kong
8 h-index
8 publications
805 citations
South China University of Technology
Guangzhou, China
8 h-index
24 publications
2.1K citations
Dalhousie University
Halifax, Canada
8 h-index
16 publications
395 citations
Poznań University of Technology
Poznan, Poland
7 h-index
11 publications
318 citations
Tsinghua University
Beijing, China
7 h-index
17 publications
613 citations
1–8 of 274
Venues
- IEEE Transactions on Evolutionary Computation
23 publications · 2.7K citations
19
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- Information Sciences
10 publications · 1.4K citations
10
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- IEEE Transactions on Cybernetics
8 publications · 629 citations
8
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- Evolutionary Computation
8 publications · 298 citations
8
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- Soft Computing
8 publications · 260 citations
8
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