Optimal Computing Budget Allocation

Optimal Computing Budget Allocation is a methodological framework within simulation-based optimization that systematically apportions a limited computational budget across candidate solutions to maximize the probability of selecting the best design through statistical discrimination.

99

Publications

5.5K

Citations

191

Authors

85

Institutions

Publications per year

2017–2026

23

Authors

191

  1. LH
    Loo Hay Lee

    National University of Singapore, Singapore

    29 publications · 1.4K citations

    21

    h-index

  2. CC
    Chun‐Hung Chen

    George Mason University, United States

    29 publications · 1.4K citations

    20

    h-index

  3. MC
    Michael C. Fu

    University of Maryland, College Park, United States

    11 publications · 686 citations

    11

    h-index

  4. EP
    Ek Peng Chew

    National University of Singapore, Singapore

    12 publications · 421 citations

    11

    h-index

  5. HX
    Hui Xiao

    Southwestern University of Finance and Economics, China

    7 publications · 392 citations

    7

    h-index

1–5 of 191

Venues

  1. IEEE Transactions on Automatic Control

    10 publications · 428 citations

    10

    h-index

  2. IIE Transactions

    5 publications · 226 citations

    5

    h-index

  3. 5

    h-index

  4. Winter Simulation Conference

    Conference · 5 publications · 225 citations

    5

    h-index

  5. Automatica

    4 publications · 231 citations

    4

    h-index

1–5