Niching Methods

Niching Methods is a class of evolutionary optimization techniques that preserve multiple stable subpopulations (niches) by modifying selection, reproduction, or fitness assignment so that search resources are distributed across distinct regions of the fitness landscape instead of converging to a single dominant solution.

206

Publications

15.2K

Citations

443

Authors

210

Institutions

Publications per year

2017–2026

69

Authors

443

  1. JZ
    Jun Zhang

    Sun Yat-sen University, China

    16 publications · 1.5K citations

    15

    h-index

  2. KD
    Kalyanmoy Deb

    Michigan State University, United States

    10 publications · 929 citations

    10

    h-index

  3. DE
    David E. Goldberg

    University of Illinois Urbana-Champaign, United States

    8 publications · 653 citations

    8

    h-index

  4. YG
    Yue‐Jiao Gong

    South China University of Technology, China

    8 publications · 360 citations

    8

    h-index

  5. XL
    Xiaodong Li

    RMIT University, Australia

    8 publications · 1.4K citations

    8

    h-index

1–5 of 443

Venues

  1. IEEE Transactions on Evolutionary Computation

    18 publications · 4K citations

    18

    h-index

  2. IEEE Transactions on Cybernetics

    10 publications · 1.1K citations

    10

    h-index

  3. IEEE Transactions on Magnetics

    10 publications · 397 citations

    10

    h-index

  4. Information Sciences

    8 publications · 772 citations

    8

    h-index

  5. Swarm and Evolutionary Computation

    8 publications · 259 citations

    8

    h-index

1–5