Generational Genetic Algorithms

Generational Genetic Algorithm is a type of genetic algorithm in which an entire population is replaced by a new generation of offspring in each iteration, distinguished from steady-state variants by its complete replacement of the parent population.

73

Publications

5.4K

Citations

192

Authors

102

Institutions

Publications per year

2017–2026

10

Variants

Generational Genetic Algorithm

Authors

192

  1. GD
    Grégoire Danoy

    University of Luxembourg, Luxembourg

    2 publications · 23 citations

    2

    h-index

  2. TC
    Terence C. Fogarty

    University of the West of England, United Kingdom

    2 publications · 144 citations

    2

    h-index

  3. SJ
    Sushil J. Louis

    University of Nevada, Reno, United States

    2 publications · 61 citations

    2

    h-index

  4. PB
    Pascal Bouvry

    University of Luxembourg, Luxembourg

    2 publications · 23 citations

    2

    h-index

  5. FV
    Frank Vavak

    University of the West of England, United Kingdom

    2 publications · 144 citations

    2

    h-index

1–5 of 192

Venues

  1. IEEE Transactions on Evolutionary Computation

    3 publications · 523 citations

    3

    h-index

  2. Engineering Optimization

    1 publications · 41 citations

    1

    h-index

  3. Defense Technical Information Center (DTIC)

    Repository · 1 publications · 1.3K citations

    1

    h-index

  4. Intelligent Decision Technologies

    1 publications · 14 citations

    1

    h-index

  5. PLoS ONE

    1 publications · 101 citations

    1

    h-index

1–5