Improved Complexity Analysis of Full Nesterov–Todd Step Feasible Interior-Point Method for Symmetric Optimization

G. Q. Wang (), L. C. Kong (), J. Y. Tao () and G. Lesaja ()
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G. Q. Wang: Shanghai University of Engineering Science
L. C. Kong: Beijing Jiaotong University
J. Y. Tao: Loyola University Maryland
G. Lesaja: Yasar University

Journal of Optimization Theory and Applications, 2015, vol. 166, issue 2, No 12, 588-604

Abstract: Abstract In this paper, an improved complexity analysis of full Nesterov–Todd step feasible interior-point method for symmetric optimization is considered. Specifically, we establish a sharper quadratic convergence result using several new results from Euclidean Jordan algebras, which leads to a wider quadratic convergence neighbourhood of the central path for the iterates in the algorithm. Furthermore, we derive the currently best known iteration bound for full Nesterov–Todd step feasible interior-point method.

Keywords: Interior-point methods; Euclidean Jordan algebras; Linear optimization over symmetric cones; Full Nesterov–Todd step; Polynomial complexity; 90C05; 90C51 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10957-014-0696-2

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