Novel update techniques for the revised simplex method

Qi Huangfu, Julian Hall

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

This paper introduces three novel techniques for updating the invertible representation of the basis matrix when solving practical sparse linear programming (LP) problems using a high performance implementation of the dual revised simplex method, being of particular value when suboptimization is used. Two are variants of the product form update and the other permits multiple Forrest-Tomlin updates to be performed. Computational results show that one of the product form variants is significantly more efficient than the traditional approach, with its performance approaching that of the Forrest-Tomlin update for some problems. The other is less efficient, but valuable in the context of the dual revised simplex method with suboptimization. Results show that the multiple Forrest-Tomlin updates are performed with no loss of serial efficiency.
Original languageEnglish
Pages (from-to)587-608
Number of pages21
JournalComputational optimization and applications
Issue number3
Early online date23 Aug 2014
Publication statusPublished - Apr 2015

Keywords / Materials (for Non-textual outputs)

  • 90C05 Linear programming
  • 90C06 Large-scale problems in mathematical programming
  • 65K05 Numerical mathematical programming methods


Dive into the research topics of 'Novel update techniques for the revised simplex method'. Together they form a unique fingerprint.

Cite this