返回
The minimum mean cycle-canceling algorithm for linear programs
DOI:10.1016/j.ejor.2021.09.022.png)
摘要
En 中文
This paper presents the properties of the minimum mean cycle-canceling algorithm for solving linear programming models. Originally designed for solving network flow problems for which it runs in strongly polynomial time, most of its properties are preserved. This is at the price of adapting the fundamental decomposition theorem of a network flow solution together with various definitions: that of a cycle and the way to calculate its cost, the residual problem, and the improvement factor at the end of a phase. We also use the primal and dual necessary and sufficient optimality conditions stated on the residual problem for establishing the pricing step giving its name to the algorithm. It turns out that the successive solutions need not be basic, there are no degenerate pivots, and the improving directions are potentially interior in addition to those on edges. For solving an m x n linear program, it requires a pseudo-polynomial number O (n A) of so-called phases, where A depends on the number of rows and the coefficient matrix. (c) 2021 Elsevier B.V. All rights reserved.
Keyword:
Linear program
Residual problem
Cycle cancellation
Complexity analysis
Interior direction
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W

