Interior-point algorithm for linear optimization based on a new trigonometric kernel function

被引：31

作者：

Li, Xin ^{[1
]}

Zhang, Mingwang ^{[1
]}

机构：

[1] China Three Gorges Univ, Coll Sci, Yi Chang 443002, Peoples R China

来源：

OPERATIONS RESEARCH LETTERS | 2015年 / 43卷 / 05期

关键词：

Linear optimization; Kernel function; Interior-point algorithm; Large-update; Polynomial complexity;

D O I：

10.1016/j.orl.2015.06.013

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

In this paper, we present a new primal-dual interior-point algorithm for linear optimization based on a trigonometric kernel function. By simple analysis, we derive the worst case complexity for a large-update primal-dual interior-point method based on this kernel function. This complexity estimate improves a result from El Ghami et al. (2012) and matches the one obtained in Reza Peza Peyghami et al. (2014). (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：471 / 475

页数：5

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