Indicator-based Optimization

Indicator-Based Optimization is a multi-objective optimization paradigm that belongs to the class of evolutionary algorithms, distinguished by its use of a quantitative performance indicator to guide the selection and evolution of solutions toward the Pareto-optimal front.

147

Publications

9.6K

Citations

410

Authors

215

Institutions

Publications per year

2017–2026

81

Authors

410

  1. HI
    Hisao Ishibuchi

    Osaka Prefecture University, Japan

    11 publications · 1.3K citations

    11

    h-index

  2. CA
    Carlos A. Coello Coello

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

    7 publications · 265 citations

    7

    h-index

  3. TF
    Tobias Friedrich

    Hasso Plattner Institute, Germany

    6 publications · 268 citations

    6

    h-index

  4. XY
    Xin Yao

    University of Birmingham, United Kingdom

    6 publications · 641 citations

    6

    h-index

  5. YN
    Yusuke Nojima

    Osaka Prefecture University, Japan

    5 publications · 329 citations

    5

    h-index

1–5 of 410

Venues

  1. IEEE Transactions on Evolutionary Computation

    15 publications · 3.3K citations

    15

    h-index

  2. Swarm and Evolutionary Computation

    6 publications · 235 citations

    6

    h-index

  3. Applied Soft Computing

    6 publications · 284 citations

    6

    h-index

  4. Information Sciences

    5 publications · 160 citations

    5

    h-index

  5. Ecological Indicators

    5 publications · 202 citations

    5

    h-index

1–5