Multi-objective Robust Optimization

Multi-Objective Robust Optimization is a mathematical optimization framework that integrates multiple conflicting objectives with uncertainty handling mechanisms, distinguishing itself from single-objective or deterministic optimization approaches by simultaneously seeking Pareto-optimal solutions that are insensitive to variations in uncertain parameters.

493

Publications

28.7K

Citations

1.5K

Authors

578

Institutions

Publications per year

2017–2026

281

Authors

1.5K

  1. SA
    Shapour Azarm

    University of Maryland, College Park, United States

    10 publications · 648 citations

    10

    h-index

  2. AS
    Anita Schöbel

    University of Göttingen, Germany

    6 publications · 594 citations

    6

    h-index

  3. MS
    Mir Saman Pishvaee

    Iran University of Science and Technology, Iran

    5 publications · 292 citations

    5

    h-index

  4. AA
    Ali Almansoori

    University of Waterloo, Canada

    4 publications · 108 citations

    4

    h-index

  5. ZC
    Zhe Chen

    Aalborg University, Denmark

    4 publications · 95 citations

    4

    h-index

1–5 of 1.5K

Venues

  1. Energy

    15 publications · 752 citations

    15

    h-index

  2. European Journal of Operational Research

    14 publications · 2K citations

    14

    h-index

  3. Structural and Multidisciplinary Optimization

    16 publications · 977 citations

    13

    h-index

  4. Computers & Industrial Engineering

    14 publications · 751 citations

    13

    h-index

  5. Journal of Cleaner Production

    13 publications · 956 citations

    13

    h-index

1–5