Risk-neutral Optimization

Risk-Neutral Optimization is an optimization framework in decision theory that, unlike risk-averse or risk-seeking approaches, evaluates uncertain outcomes based solely on their expected values, disregarding the variability or higher moments of the outcome distribution.

57

Publications

6K

Citations

126

Authors

84

Institutions

Publications per year

2017–2026

20

Authors

126

  1. SC
    Sungyong Choi

    Rutgers, The State University of New Jersey, United States

    3 publications · 267 citations

    3

    h-index

  2. RC
    Rolando Cavazos–Cadena

    Universidad Autónoma Agraria Antonio Narro, Mexico

    3 publications · 56 citations

    3

    h-index

  3. AR
    Andrzej Ruszczyński

    Rutgers, The State University of New Jersey, United States

    3 publications · 267 citations

    3

    h-index

  4. SA
    Stephen A. Woodbury

    W.E. Upjohn Institute for Employment Research, United States

    2 publications · 79 citations

    2

    h-index

  5. CD
    Carl Davidson

    Eaton (United States), United States

    2 publications · 79 citations

    2

    h-index

1–5 of 126

Venues

  1. Operations Research

    5 publications · 548 citations

    5

    h-index

  2. SSRN Electronic Journal

    Repository · 4 publications · 194 citations

    4

    h-index

  3. Journal of Political Economy

    JPE · 3 publications · 1.8K citations

    3

    h-index

  4. International Journal of Production Research

    3 publications · 185 citations

    3

    h-index

  5. Management Science

    2 publications · 1.8K citations

    2

    h-index

1–5