Knee Point Optimization

Knee Point Optimization is a solution selection strategy within continuous multi-criteria optimization that identifies the most preferred compromise solution by pinpointing the point of maximum marginal improvement on the Pareto front, where further gains in one objective yield diminishing returns relative to losses in others.

30

Publications

2.4K

Citations

93

Authors

55

Institutions

Publications per year

2017–2026

21

Authors

93

  1. YJ
    Yaochu Jin

    University of Surrey, United Kingdom

    4 publications · 1K citations

    4

    h-index

  2. GG
    Gary G. Yen

    Oklahoma State University, United States

    2 publications · 323 citations

    2

    h-index

  3. GD
    Gaurav Dhiman

    Graphic Era University, India

    2 publications · 54 citations

    2

    h-index

  4. MO
    Markus Olhofer

    Honda (Germany), Germany

    2 publications · 96 citations

    2

    h-index

  5. CH
    C. Hsein Juang

    Clemson University, United States

    2 publications · 73 citations

    2

    h-index

1–5 of 93

Venues

  1. IEEE Transactions on Evolutionary Computation

    2 publications · 1.1K citations

    2

    h-index

  2. International Journal of Vehicle Design

    IJVD · 2 publications · 54 citations

    2

    h-index

  3. IEEE Transactions on Industrial Informatics

    1 publications · 47 citations

    1

    h-index

  4. 1

    h-index

  5. Complexity

    1 publications · 30 citations

    1

    h-index

1–5