Co-evolutionary Genetic Algorithms

Co-Evolutionary Genetic Algorithms is a computational optimization paradigm within evolutionary algorithms that simultaneously evolves multiple populations of candidate solutions, where the fitness evaluation of individuals in one population depends on their interaction with individuals from other populations, thereby enabling bidirectional adaptation and joint improvement across interdependent subproblems.

86

Publications

3.4K

Citations

226

Authors

117

Institutions

Publications per year

2017–2026

24

Variants

Co-evolutionary GasCoevolutionary GasCoevolutionary Genetic Algorithms

Authors

226

  1. SS
    Sandip Sen

    University of Tulsa, United States

    3 publications · 48 citations

    3

    h-index

  2. XZ
    Xiaoping Zeng

    Chongqing University, China

    2 publications · 35 citations

    2

    h-index

  3. HJ
    Hélio J. C. Barbosa

    Laboratório Nacional de Computação Científica, Brazil

    2 publications · 91 citations

    2

    h-index

  4. ME
    Mohammad Ebrahim Shiri

    Amirkabir University of Technology, Iran

    2 publications · 62 citations

    2

    h-index

  5. CW
    Chao Wang

    Anhui University, China

    2 publications · 55 citations

    2

    h-index

1–5 of 226

Venues

  1. Applied Soft Computing

    6 publications · 371 citations

    6

    h-index

  2. Expert Systems with Applications

    4 publications · 267 citations

    4

    h-index

  3. International Journal of Production Research

    4 publications · 78 citations

    4

    h-index

  4. 3

    h-index

  5. Information Sciences

    3 publications · 215 citations

    3

    h-index

1–5