Metamodel-assisted Optimization

Metamodel-Assisted Optimization is a surrogate-assisted optimization approach that employs a metamodel as an approximate fitness landscape to guide the search process, thereby reducing the computational burden associated with evaluating expensive objective functions.

249

Publications

20.3K

Citations

590

Authors

264

Institutions

Publications per year

2017–2026

92

Authors

590

  1. KC
    Kyriakos C. Giannakoglou

    National Technical University of Athens, Greece

    12 publications · 272 citations

    11

    h-index

  2. PJ
    Ping Jiang

    Huazhong University of Science and Technology, China

    9 publications · 380 citations

    9

    h-index

  3. XS
    Xinyu Shao

    Huazhong University of Science and Technology, China

    9 publications · 380 citations

    9

    h-index

  4. QZ
    Qi Zhou

    Huazhong University of Science and Technology, China

    8 publications · 332 citations

    8

    h-index

  5. LS
    Leshi Shu

    Huazhong University of Science and Technology, China

    6 publications · 266 citations

    6

    h-index

1–5 of 590

Venues

  1. Structural and Multidisciplinary Optimization

    18 publications · 2.3K citations

    15

    h-index

  2. Engineering Optimization

    15 publications · 555 citations

    13

    h-index

  3. Journal of Mechanical Design

    10 publications · 2.3K citations

    10

    h-index

  4. Engineering Computations

    5 publications · 97 citations

    5

    h-index

  5. AIAA Journal

    5 publications · 1.5K citations

    5

    h-index

1–5