Pareto Optimal Selection

Pareto Optimal Selection is a multi-trait selection strategy that identifies solutions in the Pareto frontier, where no single trait can be improved without degrading at least one other trait.

125

Publications

5.2K

Citations

409

Authors

206

Institutions

Publications per year

2017–2026

62

Authors

409

  1. GP
    Gade Pandu Rangaiah

    National University of Singapore, Singapore

    3 publications · 171 citations

    3

    h-index

  2. WD
    Wilfried De Corte

    Ghent University, Belgium

    2 publications · 61 citations

    2

    h-index

  3. DN
    David Nowicki

    University of North Texas, United States

    2 publications · 246 citations

    2

    h-index

  4. BY
    Bo Yang

    Chongqing University, China

    2 publications · 93 citations

    2

    h-index

  5. UK
    Uday Kumar

    Luleå University of Technology, Sweden

    2 publications · 246 citations

    2

    h-index

1–5 of 409

Venues

  1. 5

    h-index

  2. IEEE Transactions on Industrial Informatics

    3 publications · 140 citations

    3

    h-index

  3. Expert Systems with Applications

    3 publications · 131 citations

    3

    h-index

  4. Journal of Cleaner Production

    3 publications · 192 citations

    3

    h-index

  5. Biomedical Signal Processing and Control

    2 publications · 59 citations

    2

    h-index

1–5