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A second order Mehrotra-type predictor-corrector algorithm for semidefinite optimization

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Abstract

Mehrotra-type predictor-corrector algorithm is one of the most effective primal-dual interiorpoint methods. This paper presents an extension of the recent variant of second order Mehrotra-type predictor-corrector algorithm that was proposed by Salahi, et al. (2006) for linear optimization. Based on the NT direction as Newton search direction, it is shown that the iteration-complexity bound of the algorithm for semidefinite optimization is {ie1108-1}, which is similar to that of the corresponding algorithm for linear optimization.

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Authors and Affiliations

  1. College of Science, China Three Gorges University, Yichang, 443002, China

    Mingwang Zhang

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  1. Mingwang Zhang
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Correspondence to Mingwang Zhang.

Additional information

This research was supported by Natural Science Foundation of Hubei Province under Grant No. 2008CDZ047.

This paper was recommended for publication by Editor Shouyang WANG.

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Zhang, M. A second order Mehrotra-type predictor-corrector algorithm for semidefinite optimization. J Syst Sci Complex 25, 1108–1121 (2012). https://doi.org/10.1007/s11424-012-0317-9

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  • DOI: https://doi.org/10.1007/s11424-012-0317-9

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