Robust Goal Programming

Robust Goal Programming is a goal programming approach that incorporates uncertainty sets or variability in parameters to ensure solution feasibility and performance across a range of plausible scenarios, thereby distinguishing itself from conventional goal programming methods by explicitly addressing data uncertainty and model robustness.

15

Publications

511

Citations

39

Authors

28

Institutions

Publications per year

2017–2026

10

Authors

39

  1. RW
    Robert W. Hanks

    U.S. Air Force Institute of Technology, United States

    2 publications · 48 citations

    2

    h-index

  2. BJ
    Brian J. Lunday

    U.S. Air Force Institute of Technology, United States

    2 publications · 48 citations

    2

    h-index

  3. JD
    Jeffery D. Weir

    U.S. Air Force Institute of Technology, United States

    2 publications · 48 citations

    2

    h-index

  4. XB
    Xuejie Bai

    Hebei Agricultural University, China

    2 publications · 130 citations

    2

    h-index

  5. AG
    Alireza Ghahtarani

    Islamic Azad University of Zanjan, Iran

    1 publications · 44 citations

    1

    h-index

1–5 of 39

Venues

  1. Computers & Industrial Engineering

    2 publications · 130 citations

    2

    h-index

  2. IEEE Access

    1 publications · 43 citations

    1

    h-index

  3. Omega

    1 publications · 23 citations

    1

    h-index

  4. European J of Industrial Engineering

    EJIE · 1 publications · 17 citations

    1

    h-index

  5. 1

    h-index

1–5