Adaptive Robust Optimization

Adaptive Robust Optimization is a mathematical optimization framework that iteratively adjusts decision policies in response to realized uncertainties, distinguishing itself from static robust optimization by incorporating adaptive responses to evolving information.

124

Publications

9.7K

Citations

320

Authors

172

Institutions

Publications per year

2017–2026

89

Authors

320

  1. FY
    Fengqi You

    Cornell University, United States

    8 publications · 655 citations

    8

    h-index

  2. ÁL
    Álvaro Lorca

    Pontificia Universidad Católica de Chile, Chile

    7 publications · 837 citations

    7

    h-index

  3. CN
    Chao Ning

    Cornell University, United States

    7 publications · 580 citations

    7

    h-index

  4. MA
    Mehrdad Aghamohamadi

    Flinders University, Australia

    5 publications · 213 citations

    5

    h-index

  5. XA
    Xu Andy Sun

    Georgia Institute of Technology, United States

    5 publications · 2.4K citations

    5

    h-index

1–5 of 320

Venues

  1. IEEE Transactions on Power Systems

    18 publications · 3.7K citations

    15

    h-index

  2. IEEE Transactions on Smart Grid

    9 publications · 868 citations

    9

    h-index

  3. IEEE Transactions on Sustainable Energy

    TSTE · 9 publications · 883 citations

    9

    h-index

  4. Applied Energy

    6 publications · 292 citations

    6

    h-index

  5. Computers & Chemical Engineering

    5 publications · 171 citations

    5

    h-index

1–5