Chance-constrained Programming With Recourse

Chance-Constrained Programming with Recourse is a stochastic optimization framework that belongs to the class of decision-making models under uncertainty, distinguished by its integration of probabilistic constraints to ensure feasibility with a specified confidence level and the inclusion of adaptive corrective actions taken after the realization of random parameters.

25

Publications

1.4K

Citations

39

Authors

29

Institutions

Publications per year

2017–2026

1

Authors

39

  1. SS
    Suvrajeet Sen

    University of Arizona, United States

    3 publications · 123 citations

    3

    h-index

  2. RS
    Rüdiger Schultz

    University of Duisburg-Essen, Germany

    3 publications · 289 citations

    3

    h-index

  3. JR
    John R. Birge

    University of Chicago, United States

    2 publications · 389 citations

    2

    h-index

  4. RJ
    Roger J.‐B. Wets

    University of California, Davis, United States

    2 publications · 183 citations

    2

    h-index

  5. HE
    Howard E. Thompson

    University of Wisconsin–Madison, United States

    2 publications · 99 citations

    2

    h-index

1–5 of 39

Venues

  1. Mathematical Programming

    6 publications · 719 citations

    6

    h-index

  2. Management Science

    3 publications · 142 citations

    3

    h-index

  3. European Journal of Operational Research

    3 publications · 104 citations

    3

    h-index

  4. Annals of Operations Research

    2 publications · 85 citations

    2

    h-index

  5. IEEE Power Engineering Review

    1 publications · 47 citations

    1

    h-index

1–5