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A new second-order corrector interior-point algorithm for semidefinite programming

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Abstract

In this paper, we propose a second-order corrector interior-point algorithm for semidefinite programming (SDP). This algorithm is based on the wide neighborhood. The complexity bound is \({O(\sqrt{n}L)}\) for the Nesterov-Todd direction, which coincides with the best known complexity results for SDP. To our best knowledge, this is the first wide neighborhood second-order corrector algorithm with the same complexity as small neighborhood interior-point methods for SDP. Some numerical results are provided as well.

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Authors and Affiliations

  1. Department of Mathematics, Xidian University, Xi’an, People’s Republic of China

    Changhe Liu & Hongwei Liu

  2. Department of Applied Mathematics, Henan University of Science and Technology, Luoyang, People’s Republic of China

    Changhe Liu

Authors
  1. Changhe Liu
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  2. Hongwei Liu
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Correspondence to Changhe Liu.

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Liu, C., Liu, H. A new second-order corrector interior-point algorithm for semidefinite programming. Math Meth Oper Res 75, 165–183 (2012). https://doi.org/10.1007/s00186-012-0379-4

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  • DOI: https://doi.org/10.1007/s00186-012-0379-4

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