Annals of Operations Research

, Volume 43, Issue 1, pp 33–47 | Cite as

A fast LU update for linear programming

  • Leena M. Suhl
  • Uwe H. Suhl
Sparse Simplex Methods


This paper discusses sparse matrix kernels of simplex-based linear programming software. State-of-the-art implementations of the simplex method maintain an LU factorization of the basis matrix which is updated at each iteration. The LU factorization is used to solve two sparse sets of linear equations at each iteration. We present new implementation techniques for a modified Forrest-Tomlin LU update which reduce the time complexity of the update and the solution of the associated sparse linear systems. We present numerical results on Netlib and other real-life LP models.


Linear System Linear Equation Time Complexity Programming Software Simplex Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© J.C. Baltzer AG, Science Publishers 1993

Authors and Affiliations

  • Leena M. Suhl
    • 1
  • Uwe H. Suhl
    • 2
  1. 1.Institut für Angewandte InformatikTechnische Universität BerlinBerlin 10Germany
  2. 2.Institut für WirtschaftsinformatikFreie Universität BerlinBerlin 33Germany

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