Enlarging neighborhoods of interior-point algorithms for linear programming via least values of proximity measure functions

doi:10.1016/j.apnum.2006.09.009

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	Enlarging neighborhoods of interior-point algorithms for linear programming via least values of proximity measure functions
	Zhao, Y. B.
	2007-09-01
发表期刊	APPLIED NUMERICAL MATHEMATICS
ISSN	0168-9274
卷号	57 期号:9 页码:1033-1049
摘要	It is well known that a wide-neighborhood interior-point algorithm for linear programming performs much better in implementation than its small-neighborhood counterparts. In this paper, we provide a unified way to enlarge the neighborhoods of predictor-corrector interior-point algorithms for linear programming. We prove that our methods not only enlarge the neighborhoods but also retain the so-far best known iteration complexity and superlinear (or quadratic) convergence of the original interior-point algorithms. The idea of our methods is to use the global minimizers of proximity measure functions. (C) 2006 IMACS. Published by Elsevier B.V. All rights reserved.
关键词	linear programming interior-point algorithms iteration complexity neighborhoods
DOI	10.1016/j.apnum.2006.09.009
语种	英语
WOS研究方向	Mathematics
WOS类目	Mathematics, Applied
WOS记录号	WOS:000248182700005
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/4373
专题	中国科学院数学与系统科学研究院
通讯作者	Zhao, Y. B.
作者单位	Chinese Acad Sci, AMSS, Inst Appl Math, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Y. B.. Enlarging neighborhoods of interior-point algorithms for linear programming via least values of proximity measure functions[J]. APPLIED NUMERICAL MATHEMATICS,2007,57(9):1033-1049.
APA	Zhao, Y. B..(2007).Enlarging neighborhoods of interior-point algorithms for linear programming via least values of proximity measure functions.APPLIED NUMERICAL MATHEMATICS,57(9),1033-1049.
MLA	Zhao, Y. B.."Enlarging neighborhoods of interior-point algorithms for linear programming via least values of proximity measure functions".APPLIED NUMERICAL MATHEMATICS 57.9(2007):1033-1049.