Posterior Constraint Selection for Nonnegative Linear Programming

• 作者: Alireza Noroziroshan H. W. Corley Jay M. Rosenberger
• 来源期刊: 美国运筹学期刊(英文)
• 学科: 数学
• 关键词: LINEAR PROGRAMMING NONNEGATIVE LINEAR PROGRAMMING Large-Scale Problems Active Set Methods CONSTRAINT SELECTION POSTERIOR Method COSTs
• 年，卷（期）: 2017,（1）
• 页码范围: 26-40
• 页数: 15页
• 分类号: O1

摘要

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.