Interval Robust Optimization

Interval Robust Optimization is a robust optimization method that accounts for uncertainty in design parameters and constraints by modeling them as bounded intervals, thereby ensuring feasible and optimal solutions under all possible realizations within the specified interval bounds.

96

Publications

4.4K

Citations

269

Authors

136

Institutions

Publications per year

2017–2026

38

Variants

Interval-based Robust Optimization

Authors

269

  1. RM
    Roberto Montemanni

    Dalle Molle Institute for Artificial Intelligence Research, Switzerland

    7 publications · 576 citations

    7

    h-index

  2. GH
    Guohe Huang

    University of Regina, Canada

    5 publications · 80 citations

    5

    h-index

  3. SA
    Shapour Azarm

    University of Maryland, College Park, United States

    5 publications · 132 citations

    5

    h-index

  4. LM
    Luca Maria Gambardella

    Dalle Molle Institute for Artificial Intelligence Research, Switzerland

    5 publications · 421 citations

    5

    h-index

  5. ML
    Mian Li

    Shanghai Jiao Tong University, China

    4 publications · 144 citations

    4

    h-index

1–5 of 269

Venues

  1. Structural and Multidisciplinary Optimization

    5 publications · 137 citations

    5

    h-index

  2. Applied Energy

    5 publications · 329 citations

    5

    h-index

  3. Journal of Mechanical Design

    4 publications · 125 citations

    4

    h-index

  4. Engineering Optimization

    3 publications · 47 citations

    3

    h-index

  5. Computers & Operations Research

    3 publications · 155 citations

    3

    h-index

1–5