A New Polynomial Interior-Point Algorithm for Monotone Mixed Linear Complementarity Problem

被引：0

作者：

Wang, Guoqiang ^{[1
]}

Cai, Xinzhong ^{[1
]}

Yue, Yujing ^{[1
]}

机构：

[1] Shanghai Univ Engn Sci, Coll Adv Vocat Technol, Shanghai 200437, Peoples R China

来源：

ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 7, PROCEEDINGS | 2008年

关键词：

Mixed linear complementarity problem; interior-point methods; small-update method; iteration bound;

D O I：

10.1109/ICNC.2008.245

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper a new polynomial interior-point algorithm for monotone mixed linear complementarity problem is presented. The algorithm is based on a new technique for finding a class of search directions and the strategy of the central path. At each iteration, we use only full-Newton step. Moreover we obtain the currently best known iteration bound for the algorithm with small-update method, namely, O(root n log n/is an element of), which is as good as the linear analogue.

引用

页码：450 / 454

页数：5

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