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Bixby, R.E., Gregory, J.W., Lustig, I.J., Marsten, R.E. and Shanno, D.F. (1992) Very Large-Scale Linear Programming: A Case Study in Combining Interior Point and Simplex Methods. Operations Research, 40, 885-897.
https://doi.org/10.1287/opre.40.5.885

has been cited by the following article:

• TITLE: Posterior Constraint Selection for Nonnegative Linear Programming

  AUTHORS: H. W. Corley, Alireza Noroziroshan, Jay M. Rosenberger

  KEYWORDS: Linear Programming, Nonnegative Linear Programming, Large-Scale Problems, Active Set Methods, Constraint Selection, Posterior Method, COSTs

  JOURNAL NAME: American Journal of Operations Research, Vol.7 No.1, January 11, 2017

  ABSTRACT: Posterior constraint optimal selection techniques (COSTs) are developed for nonnegative linear programming problems (NNLPs), and a geometric interpretation is provided. The posterior approach is used in both a dynamic and non-dynamic active-set framework. The computational performance of these methods is compared with the CPLEX standard linear programming algorithms, with two most-violated constraint approaches, and with previously developed COST algorithms for large-scale problems.