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      Generalized column generation for linear programming

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      Author
      Oğuz, O.
      Date
      2002
      Source Title
      Management Science
      Print ISSN
      0025-1909
      Publisher
      Institute for Operations Research and the Management Sciences (INFORMS)
      Volume
      48
      Issue
      3
      Pages
      444 - 452
      Language
      English
      Type
      Article
      Item Usage Stats
      128
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      Abstract
      Column generation is a well-known and widely practiced technique for solving linear programs with too many variables or constraints to include in the initial formulation explicitly. Instead, the required column information is generated at each iteration of the simplex algorithm. This paper shows that, even if the number of variables is low enough for explicit inclusion in the model with the available technology, it may still be more efficient to resort to column generation for some class of problems.
      Keywords
      Column generation
      Linear programming
      Simplex algorithm
      Algorithms
      Integer programming
      Linear programming
      Mathematical models
      Optimization
      Column generation
      Small scale optimization
      Variables
      Management science
      Permalink
      http://hdl.handle.net/11693/24735
      Published Version (Please cite this version)
      https://doi.org/10.1287/mnsc.48.3.444.7729
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