Surrogate Model Management

Surrogate Model Management is a methodological framework within surrogate-based optimization that orchestrates the construction, updating, selection, and validation of surrogate models to balance computational efficiency and solution accuracy in iterative design processes.

44

Publications

2.9K

Citations

124

Authors

71

Institutions

Publications per year

2017–2026

26

Authors

124

  1. YJ
    Yaochu Jin

    University of Surrey, United Kingdom

    4 publications · 589 citations

    4

    h-index

  2. AL
    Alison L. Marsden

    Stanford University, United States

    3 publications · 321 citations

    3

    h-index

  3. ME
    Michael Eldred

    Sandia National Laboratories, United States

    3 publications · 400 citations

    3

    h-index

  4. QL
    Qiqi Liu

    University of Surrey, United Kingdom

    2 publications · 96 citations

    2

    h-index

  5. SL
    Sébastien Le Digabel

    Polytechnique Montréal, Canada

    2 publications · 75 citations

    2

    h-index

1–5 of 124

Venues

  1. IEEE Transactions on Evolutionary Computation

    6 publications · 636 citations

    6

    h-index

  2. Complex & Intelligent Systems

    2 publications · 111 citations

    2

    h-index

  3. Optimization and Engineering

    2 publications · 175 citations

    2

    h-index

  4. 2

    h-index

  5. IEEE Transactions on Cybernetics

    2 publications · 313 citations

    2

    h-index

1–5