Static Robust Optimization

Static Robust Optimization is a robust optimization approach that belongs to the class of static decision-making models, distinguished by its requirement for all decision variables to be determined prior to the realization of uncertain parameters, thereby committing to a single immutable solution under all possible uncertainty scenarios.

25

Publications

1.7K

Citations

74

Authors

31

Institutions

Publications per year

2017–2026

9

Authors

74

  1. DB
    Dimitris Bertsimas

    Massachusetts Institute of Technology, United States

    4 publications · 408 citations

    4

    h-index

  2. HJ
    Howard Jay Siegel

    Colorado State University, United States

    3 publications · 135 citations

    3

    h-index

  3. DD
    Dick den Hertog

    Tilburg University, Netherlands

    3 publications · 252 citations

    3

    h-index

  4. AA
    Anthony A. Maciejewski

    Colorado State University, United States

    3 publications · 135 citations

    3

    h-index

  5. VG
    Vineet Goyal

    Columbia University, United States

    3 publications · 216 citations

    3

    h-index

1–5 of 74

Venues

  1. Mathematical Programming

    3 publications · 325 citations

    3

    h-index

  2. Journal of Parallel and Distributed Computing

    2 publications · 124 citations

    2

    h-index

  3. Mathematics of Operations Research

    2 publications · 154 citations

    2

    h-index

  4. Automatica

    2 publications · 136 citations

    2

    h-index

  5. INFORMS journal on computing

    1 publications · 105 citations

    1

    h-index

1–5