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.