Budgeted Uncertainty

Budgeted Uncertainty is a robust optimization framework that belongs to the class of uncertainty set formulations, distinguished by its restriction of the total number or magnitude of uncertain parameters that can simultaneously deviate from their nominal values within a predefined budget.

23

Publications

1.1K

Citations

67

Authors

57

Institutions

Publications per year

2017–2026

13

Authors

67

  1. MP
    Michaël Poss

    Centre National de la Recherche Scientifique, France

    4 publications · 173 citations

    4

    h-index

  2. AA
    Amir Ardestani-Jaafari

    University of British Columbia, Okanagan Campus, Canada

    2 publications · 150 citations

    2

    h-index

  3. AA
    Artur Alves Pessoa

    Universidade Federal Fluminense, Brazil

    2 publications · 73 citations

    2

    h-index

  4. ED
    Erick Delage

    HEC Montréal, Canada

    2 publications · 150 citations

    2

    h-index

  5. MJ
    Mohammad Javad Feizollahi

    Georgia Institute of Technology, United States

    2 publications · 72 citations

    2

    h-index

1–5 of 67

Venues

  1. European Journal of Operational Research

    3 publications · 59 citations

    3

    h-index

  2. Transportation Science

    2 publications · 164 citations

    2

    h-index

  3. IEEE Transactions on Reliability

    2 publications · 72 citations

    2

    h-index

  4. Operations Research

    2 publications · 117 citations

    2

    h-index

  5. SIAM Journal on Optimization

    1 publications · 34 citations

    1

    h-index

1–5