Recourse Models

Recourse Models is a type of stochastic optimization framework that distinguishes itself by incorporating adaptive decision-making stages, where initial decisions are followed by corrective actions in response to the realization of random variables.

236

Publications

14.3K

Citations

504

Authors

279

Institutions

Publications per year

2017–2026

64

Variants

Stochastic Programming With Recourse

Authors

504

  1. MH
    Maarten H. van der Vlerk

    University of Groningen, Netherlands

    13 publications · 385 citations

    12

    h-index

  2. RS
    Rüdiger Schultz

    University of Duisburg-Essen, Germany

    10 publications · 498 citations

    10

    h-index

  3. RJ
    Roger J.‐B. Wets

    University of California, Davis, United States

    8 publications · 788 citations

    8

    h-index

  4. WK
    Willem K. Klein Haneveld

    University of Groningen, Netherlands

    6 publications · 138 citations

    6

    h-index

  5. WR
    Walter Rei

    Université du Québec à Montréal, Canada

    4 publications · 265 citations

    4

    h-index

1–5 of 504

Venues

  1. Transportation Science

    12 publications · 914 citations

    12

    h-index

  2. Operations Research

    10 publications · 1.9K citations

    10

    h-index

  3. IEEE Transactions on Power Systems

    10 publications · 1.7K citations

    10

    h-index

  4. Mathematical Programming

    9 publications · 1.3K citations

    9

    h-index

  5. arXiv (Cornell University)

    Repository · 9 publications · 361 citations

    9

    h-index

1–5