Multi-objective Optimization Under Uncertainty

Multi-Objective Optimization Under Uncertainty is a mathematical framework within optimization theory that involves the simultaneous minimization or maximization of multiple conflicting objectives subject to uncertain parameters or probabilistic constraints.

691

Publications

30.1K

Citations

2K

Authors

805

Institutions

Publications per year

2017–2026

385

Authors

2K

  1. SA
    Shapour Azarm

    University of Maryland, College Park, United States

    8 publications · 261 citations

    8

    h-index

  2. AS
    Anita Schöbel

    University of Göttingen, Germany

    7 publications · 415 citations

    7

    h-index

  3. CY
    Chen Yang

    Beihang University, China

    6 publications · 450 citations

    6

    h-index

  4. JV
    Jan Van Impe

    KU Leuven, Belgium

    6 publications · 240 citations

    6

    h-index

  5. FL
    Filip Logist

    KU Leuven, Belgium

    5 publications · 227 citations

    5

    h-index

1–5 of 2K

Venues

  1. Energy

    30 publications · 1.5K citations

    23

    h-index

  2. European Journal of Operational Research

    23 publications · 1.2K citations

    20

    h-index

  3. Expert Systems with Applications

    20 publications · 648 citations

    16

    h-index

  4. Applied Energy

    17 publications · 851 citations

    14

    h-index

  5. Structural and Multidisciplinary Optimization

    18 publications · 410 citations

    14

    h-index

1–5