Complexity Analysis of Primal-Dual Interior-Point Methods for Linear Optimization Based on a New Parametric Kernel Function with a Trigonometric Barrier Term

X. Z. Cai, G. Q. Wang, M. El Ghami and Y. J. Yue

Abstract and Applied Analysis, 2014, vol. 2014, 1-11

Abstract:

We introduce a new parametric kernel function, which is a combination of the classic kernel function and a trigonometric barrier term, and present various properties of this new kernel function. A class of large- and small-update primal-dual interior-point methods for linear optimization based on this parametric kernel function is proposed. By utilizing the feature of the parametric kernel function, we derive the iteration bounds for large-update methods, , and small-update methods, . These results match the currently best known iteration bounds for large- and small-update methods based on the trigonometric kernel functions.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:710158

DOI: 10.1155/2014/710158

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