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Decomposition Branching for Mixed Integer Programming

Author

Listed:
  • Barış Yıldız

    (Department of Industrial Engineering, Koc University, Istanbul 34450, Turkey)

  • Natashia Boland

    (H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Martin Savelsbergh

    (H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

We introduce a novel and powerful approach for solving certain classes of mixed integer programs (MIPs): decomposition branching . Two seminal and widely used techniques for solving MIPs, branch-and-bound and decomposition, form its foundation. Computational experiments with instances of a weighted set covering problem and a regionalized p -median facility location problem with assignment range constraints demonstrate its efficacy: it explores far fewer nodes and can be orders of magnitude faster than a commercial solver and an automatic Dantzig-Wolfe approach.

Suggested Citation

  • Barış Yıldız & Natashia Boland & Martin Savelsbergh, 2022. "Decomposition Branching for Mixed Integer Programming," Operations Research, INFORMS, vol. 70(3), pages 1854-1872, May.
    • Handle: RePEc:inm:oropre:v:70:y:2022:i:3:p:1854-1872
    DOI: 10.1287/opre.2021.2210
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