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Branch-and-Price: Column Generation for Solving Huge Integer Programs

Author

Listed:
  • Cynthia Barnhart

    (Georgia Institute of Technology, Atlanta, Georgia)

  • Ellis L. Johnson

    (Georgia Institute of Technology, Atlanta, Georgia)

  • George L. Nemhauser

    (Georgia Institute of Technology, Atlanta, Georgia)

  • Martin W. P. Savelsbergh

    (Georgia Institute of Technology, Atlanta, Georgia)

  • Pamela H. Vance

    (Georgia Institute of Technology, Atlanta, Georgia)

Abstract

We discuss formulations of integer programs with a huge number of variables and their solution by column generation methods, i.e., implicit pricing of nonbasic variables to generate new columns or to prove LP optimality at a node of the branch-and-bound tree. We present classes of models for which this approach decomposes the problem, provides tighter LP relaxations, and eliminates symmetry. We then discuss computational issues and implementation of column generation, branch-and-bound algorithms, including special branching rules and efficient ways to solve the LP relaxation. We also discuss the relationship with Lagrangian duality.

Suggested Citation

  • Cynthia Barnhart & Ellis L. Johnson & George L. Nemhauser & Martin W. P. Savelsbergh & Pamela H. Vance, 1998. "Branch-and-Price: Column Generation for Solving Huge Integer Programs," Operations Research, INFORMS, vol. 46(3), pages 316-329, June.
  • Handle: RePEc:inm:oropre:v:46:y:1998:i:3:p:316-329
    DOI: 10.1287/opre.46.3.316
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    References listed on IDEAS

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