Complexity analysis of infeasible interior-point method for semidefinite optimization based on a new trigonometric kernel function

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Abstract

In this paper, a full Nesterov–Todd step infeasible interior-point method for solving semidefinite optimization problems based on a new kernel function is analyzed. In each iteration, the algorithm involves a feasibility step and several centrality steps. The centrality step is focused on Nesterov–Todd search directions, while we used a kernel function with trigonometric barrier term to induce the feasibility step. The complexity result coincides with the best-known iteration bound for infeasible interior-point methods.

Keywords

Semidefinite optimization Infeasible interior-point method Trigonometric kernel function Full Nesterov–Todd step Polynomial complexity 

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Applied MathematicsAzarbaijan Shahid Madani UniversityTabrizIran

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