Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood

作     者：Asadi, Alireza Roos, Cornelis 

作者机构：Delft Univ Technol Fac Elect Engn Comp Sci & Math POB 5031 NL-2600 GA Delft Netherlands 

出 版 物：《JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS》 (优选法理论与应用杂志)

年 卷 期：2016年第170卷第2期

页      面：562-590页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

主　　题：Linear optimization Primal-dual infeasible interior-point methods Polynomial algorithms 

摘      要：In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author. Unfortunately, despite its good numerical behavior, the theoretical convergence rate of our algorithm is worse up to square root of problem dimension.