Multiobjective Optimization

Multiobjective Optimization is a formal decision-making framework in which a single optimization problem involves multiple conflicting objectives that must be simultaneously minimized or maximized, distinguished from single-objective optimization by the necessity of achieving a compromise among incommensurable criteria.

15.8K

Publications

981.3K

Citations

27.7K

Authors

4.7K

Institutions

Publications per year

2017–2026

6.7K

Authors

27.7K

  1. YJ
    Yaochu Jin

    University of Surrey, United Kingdom

    138 publications · 24.3K citations

    69

    h-index

  2. KD
    Kalyanmoy Deb

    Michigan State University, United States

    155 publications · 90.7K citations

    64

    h-index

  3. KC
    Kay Chen Tan

    National University of Singapore, Singapore

    120 publications · 13.2K citations

    62

    h-index

  4. CA
    Carlos A. Coello Coello

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

    171 publications · 24.9K citations

    62

    h-index

  5. QZ
    Qingfu Zhang

    City University of Hong Kong, Hong Kong SAR China

    115 publications · 29.1K citations

    60

    h-index

1–5 of 27.7K

Venues

  1. IEEE Transactions on Evolutionary Computation

    421 publications · 155K citations

    149

    h-index

  2. European Journal of Operational Research

    376 publications · 30.3K citations

    88

    h-index

  3. IEEE Transactions on Cybernetics

    198 publications · 22.8K citations

    85

    h-index

  4. Applied Soft Computing

    416 publications · 22.1K citations

    75

    h-index

  5. Expert Systems with Applications

    282 publications · 18.2K citations

    73

    h-index

1–5