Fitness Function Sensitivity Analysis

Fitness Function Sensitivity Analysis is a methodological procedure that systematically evaluates the extent to which variations in the parameters or structure of a fitness function influence the behavior and outcomes of an evolutionary optimization process, thereby distinguishing it from general fitness function design by focusing on robustness and input-output responsiveness.

18

Publications

1.4K

Citations

53

Authors

24

Institutions

Publications per year

2017–2026

5

Authors

53

  1. TJ
    Tadeusz J. Kawecki

    University of Lausanne, Switzerland

    2 publications · 323 citations

    2

    h-index

  2. SC
    Stephen C. Stearns

    Yale University, United States

    2 publications · 323 citations

    2

    h-index

  3. MZ
    Martin Ziehe

    University of Göttingen, Germany

    1 publications · 30 citations

    1

    h-index

  4. JG
    Jill G. Pilkington

    University of Edinburgh, United Kingdom

    1 publications · 37 citations

    1

    h-index

  5. JH
    Jian Hu

    China Agricultural University, China

    1 publications · 77 citations

    1

    h-index

1–5 of 53

Venues

  1. Evolution

    3 publications · 360 citations

    3

    h-index

  2. Sustainable Computing Informatics and Systems

    1 publications · 22 citations

    1

    h-index

  3. Applied Artificial Intelligence

    AAI · 1 publications · 11 citations

    1

    h-index

  4. Journal of Vibration and Control

    JVC · 1 publications · 28 citations

    1

    h-index

  5. IEEE Transactions on Evolutionary Computation

    1 publications · 128 citations

    1

    h-index

1–5