A Large-Update Primal-Dual Interior-Point Method for Second-Order Cone Programming
- 作者单位
- Shandong Univ Sci & Technol, Coll Informat Sci & Engn, Qingdao 266510, Peoples R China Taishan Univ, Coll Math & Syst Sci, Tai An 271021, Shandong, Peoples R China Taishan Med Univ, Coll Informat Engn, Tai An 271000, Shandong, Peoples R China
- 刊名
- ADVANCES IN NEURAL NETWORKS - ISNN 2010, PT 1, PROCEEDINGS
- 年份
- 2010
- 卷号
- Vol.6063
- 页码
- 102
- ISSN
- 0302-9743
- 关键词
- Second-order cone programming Smoothing method Interior-point method Q-quadratic convergence Central path
- 摘要
- 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 N-infinity(-)(tau), but not necessary staying within it. However, it must stay within a wider neighborhood N(tau,beta). We show that the method has O(root rL) iteration complexity bound which is the best bound of wide neighborhood algorithm for second-order cone programming.
- 文献类型
- 期刊
- 浏览量
- 13
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被引次数
-
收录
CPCI-S