Sequential Design Optimization

Sequential Design Optimization is a methodological framework within sequential testing that iteratively refines experimental or sampling designs by dynamically selecting subsequent observations or interventions to maximize statistical efficiency or information gain under uncertainty.

177

Publications

8.3K

Citations

492

Authors

223

Institutions

Publications per year

2017–2026

41

Authors

492

  1. HH
    Hong‐Zhong Huang

    University of Electronic Science and Technology of China, China

    6 publications · 288 citations

    6

    h-index

  2. DM
    Debiao Meng

    University of Electronic Science and Technology of China, China

    6 publications · 204 citations

    6

    h-index

  3. YG
    Youguang Guo

    University of Technology Sydney, Australia

    4 publications · 192 citations

    4

    h-index

  4. XD
    Xiaoping Du

    Missouri University of Science and Technology, United States

    4 publications · 316 citations

    4

    h-index

  5. XZ
    Xudong Zhang

    University of Electronic Science and Technology of China, China

    4 publications · 191 citations

    4

    h-index

1–5 of 492

Venues

  1. Engineering Optimization

    7 publications · 259 citations

    7

    h-index

  2. Journal of Mechanical Design

    7 publications · 474 citations

    7

    h-index

  3. Structural and Multidisciplinary Optimization

    6 publications · 328 citations

    6

    h-index

  4. Technometrics

    5 publications · 1.7K citations

    5

    h-index

  5. Journal of Mechanical Science and Technology

    4 publications · 90 citations

    4

    h-index

1–5