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On Compact Formulations for Integer Programs Solved by Column Generation

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Listed:
  • Daniel Villeneuve
  • Jacques Desrosiers
  • Marco Lübbecke
  • François Soumis

Abstract

Column generation has become a powerful tool in solving large scale integer programs. It is well known that most of the often reported compatibility issues between pricing subproblem and branching rule disappear when branching decisions are based on imposing constraints on the subproblem's variables. This can be generalized to branching on variables of a so-called compact formulation. We constructively show that such a formulation always exists under mild assumptions. It has a block diagonal structure with identical subproblems, each of which contributes only one column in an integer solution. This construction has an interpretation as reversing a Dantzig-Wolfe decomposition. Our proposal opens the way for the development of branching rules adapted to the subproblem's structure and to the linking constraints. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Daniel Villeneuve & Jacques Desrosiers & Marco Lübbecke & François Soumis, 2005. "On Compact Formulations for Integer Programs Solved by Column Generation," Annals of Operations Research, Springer, vol. 139(1), pages 375-388, October.
    • Handle: RePEc:spr:annopr:v:139:y:2005:i:1:p:375-388:10.1007/s10479-005-3455-9
    DOI: 10.1007/s10479-005-3455-9
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    References listed on IDEAS

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    Cited by:

    1. Giuseppe Lancia & Paolo Serafini, 2016. "Deriving compact extended formulations via LP-based separation techniques," Annals of Operations Research, Springer, vol. 240(1), pages 321-350, May.
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    3. C Alves & J M Valério de Carvalho, 2008. "New integer programming formulations and an exact algorithm for the ordered cutting stock problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(11), pages 1520-1531, November.
    4. Ioannis Fragkos & Zeger Degraeve & Bert De Reyck, 2016. "A Horizon Decomposition Approach for the Capacitated Lot-Sizing Problem with Setup Times," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 465-482, August.

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