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An Adaptive Infeasible Interior-Point Algorithm with Full Nesterov-Todd Step for Semidefinite Optimization

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Journal of Mathematical Modelling and Algorithms in Operations Research

Abstract

We present an adaptive full Nesterov-Todd step infeasible interior-point method for semidefinite optimization. The proposed algorithm requires two types of full Nesterov-Todd steps are called, feasibility steps and centering steps, respectively. At each iteration both feasibility and optimality are reduced exactly at the same rate. In each iteration of the algorithm we use the largest possible barrier parameter value θ. The value θ varies from iteration to iteration and it lies between the two values \(\frac {1}{4n}\) and \(\frac {1}{5n}\), which results a faster algorithm.

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  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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Kheirfam, B. An Adaptive Infeasible Interior-Point Algorithm with Full Nesterov-Todd Step for Semidefinite Optimization. J Math Model Algor 14, 55–66 (2015). https://doi.org/10.1007/s10852-014-9257-9

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  • DOI: https://doi.org/10.1007/s10852-014-9257-9

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