Multiobjective Stochastic Programming

Multiobjective Stochastic Programming is a mathematical optimization framework that belongs to the class of stochastic programming models, distinguished by its simultaneous consideration of multiple conflicting objectives under uncertainty, where decision outcomes depend on random variables governed by known probability distributions.

100

Publications

5.9K

Citations

276

Authors

163

Institutions

Publications per year

2017–2026

37

Authors

276

  1. FB
    Fouad Ben Abdelaziz

    NEOMA Business School, France

    6 publications · 496 citations

    6

    h-index

  2. TN
    Taher Niknam

    Shiraz University of Technology, Iran

    4 publications · 764 citations

    4

    h-index

  3. MM
    María M. Muñoz

    Universidad de Málaga, Spain

    3 publications · 104 citations

    3

    h-index

  4. SM
    Seyed Mohammad Javad Mirzapour Al-e-Hashem

    Amirkabir University of Technology, Iran

    3 publications · 538 citations

    3

    h-index

  5. MP
    M. P. Biswal

    Indian Institute of Technology Kharagpur, India

    3 publications · 62 citations

    3

    h-index

1–5 of 276

Venues

  1. European Journal of Operational Research

    12 publications · 884 citations

    11

    h-index

  2. Fuzzy Sets and Systems

    4 publications · 131 citations

    4

    h-index

  3. IET Generation Transmission & Distribution

    4 publications · 267 citations

    4

    h-index

  4. OR Spectrum

    3 publications · 440 citations

    3

    h-index

  5. Applied Energy

    3 publications · 539 citations

    3

    h-index

1–5