Dantzig-wolfe Decomposition

Dantzig-Wolfe Decomposition is a mathematical optimization technique that decomposes a large-scale linear program into a master problem and subproblems by exploiting block-angular structure, enabling efficient solution through column generation and reformulation of the original problem into a set of simpler, linked submodels.

188

Publications

13.1K

Citations

385

Authors

191

Institutions

Publications per year

2017–2026

27

Authors

385

  1. MS
    Mohammad Shahidehpour

    Illinois Institute of Technology, United States

    7 publications · 616 citations

    7

    h-index

  2. ME
    Marco E. Lübbecke

    Technische Universität Berlin, Germany

    4 publications · 1.3K citations

    4

    h-index

  3. KA
    K.H. Abdul-Rahman

    Illinois Institute of Technology, United States

    4 publications · 157 citations

    4

    h-index

  4. JD
    Jacques Desrosiers

    HEC Montréal, Canada

    4 publications · 1.5K citations

    4

    h-index

  5. RJ
    Raf Jans

    HEC Montréal, Canada

    4 publications · 167 citations

    4

    h-index

1–5 of 385

Venues

  1. Operations Research

    24 publications · 4.6K citations

    18

    h-index

  2. Management Science

    15 publications · 1.2K citations

    14

    h-index

  3. IEEE Transactions on Power Systems

    14 publications · 1.1K citations

    14

    h-index

  4. INFORMS journal on computing

    10 publications · 738 citations

    10

    h-index

  5. Transportation Science

    6 publications · 607 citations

    6

    h-index

1–5