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Complexity analysis of a full-Newton step interior-point method for linear optimization

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Abstract

This paper concerns a short-update primal-dual interior-point method for linear optimization based on a new search direction. We apply a vector-valued function generated by a univariate function on the nonlinear equation of the system which defines the central path. The common way to obtain the equivalent form of the central path is using the square root function. In this paper we consider a new function formed by the difference of the identity map and the square root function. We apply Newton’s method in order to get the new directions. In spite of the fact that the analysis is more difficult in this case, we prove that the complexity of the algorithm is identical with the one of the best known methods for linear optimization.

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Acknowledgments

The authors gratefully acknowledge the support of the Edutus College (Collegium Talentum) and the Transylvanian Museum Society. The authors are thankful to the editor and the reviewer for their helpful suggestions that improved the presentation of this paper. We also thank Ágnes Felméri and Nóra Forró for their useful comments on the paper. The work of the third author was supported by a grant of the Romanian National Authority for Scientific Research, CNCS-UEFISCDI, project number PN-II-ID-PCE-2011-3-0024.

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  1. Faculty of Mathematics and Computer Science, Babeş-Bolyai University, No. 1 Mihail Kogălniceanu Street, 400084, Cluj-Napoca, Romania

    Zsolt Darvay, Ingrid-Magdolna Papp & Petra-Renáta Takács

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  1. Zsolt Darvay
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Correspondence to Zsolt Darvay.

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Darvay, Z., Papp, IM. & Takács, PR. Complexity analysis of a full-Newton step interior-point method for linear optimization. Period Math Hung 73, 27–42 (2016). https://doi.org/10.1007/s10998-016-0119-2

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