Robust Resource Allocation

Robust Resource Allocation is a decision-making framework that systematically allocates resources under uncertainty by optimizing performance across a wide range of plausible future scenarios while maintaining feasibility and effectiveness despite model misspecification or environmental variability.

263

Publications

11.9K

Citations

864

Authors

373

Institutions

Publications per year

2017–2026

134

Authors

864

  1. HJ
    Howard Jay Siegel

    Colorado State University, United States

    20 publications · 654 citations

    13

    h-index

  2. AA
    Anthony A. Maciejewski

    Colorado State University, United States

    20 publications · 654 citations

    13

    h-index

  3. YX
    Yongjun Xu

    Chongqing University of Posts and Telecommunications, China

    12 publications · 461 citations

    12

    h-index

  4. DW
    Derrick Wing Kwan Ng

    UNSW Sydney, Australia

    10 publications · 1.2K citations

    10

    h-index

  5. RS
    Robert Schober

    Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

    9 publications · 1.1K citations

    9

    h-index

1–5 of 864

Venues

  1. IEEE Transactions on Wireless Communications

    17 publications · 714 citations

    14

    h-index

  2. IEEE Transactions on Vehicular Technology

    11 publications · 429 citations

    10

    h-index

  3. IEEE Transactions on Communications

    10 publications · 1K citations

    10

    h-index

  4. IEEE Access

    8 publications · 179 citations

    7

    h-index

  5. Journal of Parallel and Distributed Computing

    6 publications · 228 citations

    6

    h-index

1–5