Multiobjective Niching

Multiobjective Niching is a computational optimization strategy within evolutionary algorithms that extends conventional niching methods by simultaneously preserving multiple diverse solutions across several conflicting objectives, thereby maintaining both solution diversity in the decision space and convergence in the objective space.

22

Publications

1.6K

Citations

70

Authors

33

Institutions

Publications per year

2017–2026

6

Variants

Multi-objective Niching

Authors

70

  1. KS
    Kumara Sastry

    University of Illinois Urbana-Champaign, United States

    2 publications · 114 citations

    2

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  2. MP
    Martin Pelikán

    University of Illinois Urbana-Champaign, United States

    2 publications · 114 citations

    2

    h-index

  3. DE
    David E. Goldberg

    University of Illinois Urbana-Champaign, United States

    2 publications · 114 citations

    2

    h-index

  4. TB
    Thomas Baeck

    Leiden University, Netherlands

    1 publications · 26 citations

    1

    h-index

  5. EK
    E.F. Khor

    National University of Singapore, Singapore

    1 publications · 75 citations

    1

    h-index

1–5 of 70

Venues

  1. Swarm and Evolutionary Computation

    2 publications · 60 citations

    2

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  2. 1

    h-index

  3. IEEE Transactions on Cybernetics

    1 publications · 198 citations

    1

    h-index

  4. Memetic Computing

    1 publications · 19 citations

    1

    h-index

  5. Computers & Industrial Engineering

    1 publications · 58 citations

    1

    h-index

1–5