Parallel Genetic Algorithms

Parallel Genetic Algorithms is a class of genetic algorithms that extends the basic genetic algorithm framework by executing multiple subpopulations or evolutionary operations concurrently across parallel processing units, thereby enhancing search efficiency and solution diversity through inter-population migration and distributed computation.

751

Publications

37K

Citations

1.8K

Authors

724

Institutions

Publications per year

2017–2026

105

Variants

Parallel Genetic AlgorithmPga

Authors

1.8K

  1. EA
    Enrique Alba

    Universidad de Málaga, Spain

    16 publications · 1.1K citations

    13

    h-index

  2. DE
    David E. Goldberg

    University of Illinois Urbana-Champaign, United States

    8 publications · 3.2K citations

    8

    h-index

  3. EC
    Erick Cantú‐Paz

    Lawrence Livermore National Laboratory, United States

    7 publications · 1.5K citations

    7

    h-index

  4. MM
    Mitsunori Miki

    Doshisha University, Japan

    7 publications · 238 citations

    7

    h-index

  5. TH
    Tomoyuki Hiroyasu

    Doshisha University, Japan

    7 publications · 238 citations

    7

    h-index

1–5 of 1.8K

Venues

  1. international conference on Genetic algorithms

    Conference · 14 publications · 3.8K citations

    12

    h-index

  2. Parallel Computing

    11 publications · 1.4K citations

    11

    h-index

  3. Journal of Parallel and Distributed Computing

    10 publications · 549 citations

    10

    h-index

  4. Computers & Industrial Engineering

    10 publications · 456 citations

    10

    h-index

  5. 8

    h-index

1–5