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A Corrector–Predictor Path-Following Method for Convex Quadratic Symmetric Cone Optimization

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Abstract

After a brief introduction to Euclidean Jordan algebra, we present a new corrector–predictor path-following interior-point algorithm for convex, quadratic, and symmetric cone optimization. In each iteration, the algorithm involves two kind of steps: a predictor (affine-scaling) step and a full Nesterov and Todd (centring) step. Moreover, we derive the complexity for the algorithm, and we obtain the best-known iteration bound for the small-update method.

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Acknowledgments

The author is grateful to two anonymous referees and the Editors for their constructive comments and suggestions to improve the presentation.

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Authors and Affiliations

  1. Department of Mathematics, Azarbaijan Shahid Madani University, Tabriz, I.R. Iran

    Behrouz Kheirfam

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  1. Behrouz Kheirfam
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Correspondence to Behrouz Kheirfam.

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Communicated by Florian A. Potra.

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Kheirfam, B. A Corrector–Predictor Path-Following Method for Convex Quadratic Symmetric Cone Optimization. J Optim Theory Appl 164, 246–260 (2015). https://doi.org/10.1007/s10957-014-0554-2

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