A large-update primal-dual interior-point method for second-order cone programming

Authors:
Liang Fang;Guoping He;Zengzhe Feng;Yongli Wang
Affiliations:
College of Mathematics and System Science, Taishan University, Tai'an, P.R China;College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, P.R China;College of Information Engineering, Taishan Medical University, Tai'an, P.R China;College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, P.R China
Venue:
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Year:
2010

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Abstract

A large-update primal-dual interior-point algorithm is presented for solving second order cone programming At each iteration, the iterate is always following the usual wide neighborhood $\mathcal {N}_\infty^-(\tau)$, but not necessary staying within it However, it must stay within a wider neighborhood $\mathcal {N}(\tau,\beta)$ We show that the method has $O(\sqrt{r}L)$ iteration complexity bound which is the best bound of wide neighborhood algorithm for second-order cone programming.