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A Large-Update Primal-Dual Interior-Point Method for Second-Order Cone Programming

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Advances in Neural Networks - ISNN 2010 (ISNN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6063))

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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.

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References

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Author information

Authors and Affiliations

  1. College of Mathematics and System Science, Taishan University, 271021, Tai’an, P.R. China

    Liang Fang

  2. College of Information Science and Engineering, Shandong University of Science and Technology, 266510, Qingdao, P.R. China

    Guoping He & Yongli Wang

  3. College of Information Engineering, Taishan Medical University, 271000, Tai’an, P.R. China

    Zengzhe Feng

Authors
  1. Liang Fang
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  2. Guoping He
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  3. Zengzhe Feng
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  4. Yongli Wang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China

    Liqing Zhang

  2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, 200240, Shanghai, China

    Bao-Liang Lu

  3. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water bay, Kowloon, Hong Kong, China

    James Kwok

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© 2010 Springer-Verlag Berlin Heidelberg

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Fang, L., He, G., Feng, Z., Wang, Y. (2010). A Large-Update Primal-Dual Interior-Point Method for Second-Order Cone Programming. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13278-0_14

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  • DOI: https://doi.org/10.1007/978-3-642-13278-0_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13277-3

  • Online ISBN: 978-3-642-13278-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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