Many-objective Optimization

Many-Objective Optimization is a subfield of multiobjective optimization that specifically addresses optimization problems involving four or more conflicting objectives, distinguishing it from simpler multiobjective cases by the increased complexity in trade-off analysis, solution scalability, and visualization challenges associated with higher-dimensional objective spaces.

1.1K

Publications

83.3K

Citations

2.1K

Authors

754

Institutions

Publications per year

2017–2026

730

Variants

Maoo

Authors

2.1K

  1. YJ
    Yaochu Jin

    University of Surrey, United Kingdom

    36 publications · 8.5K citations

    31

    h-index

  2. KD
    Kalyanmoy Deb

    Michigan State University, United States

    42 publications · 15.7K citations

    29

    h-index

  3. HI
    Hisao Ishibuchi

    Osaka Prefecture University, Japan

    38 publications · 3.5K citations

    25

    h-index

  4. CA
    Carlos A. Coello Coello

    Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico

    28 publications · 1.9K citations

    23

    h-index

  5. ML
    Miqing Li

    University of Birmingham, United Kingdom

    26 publications · 4K citations

    21

    h-index

1–5 of 2.1K

Venues

  1. IEEE Transactions on Evolutionary Computation

    101 publications · 30.6K citations

    68

    h-index

  2. IEEE Transactions on Cybernetics

    46 publications · 5K citations

    41

    h-index

  3. Information Sciences

    73 publications · 3.5K citations

    35

    h-index

  4. Swarm and Evolutionary Computation

    54 publications · 2K citations

    25

    h-index

  5. Applied Soft Computing

    43 publications · 1.6K citations

    24

    h-index

1–5