Title: Kernel function-based interior-point algorithms for linear optimisation

Authors: Bachir Bounibane; El Amir Djeffal

Addresses: Department of Mathematics, University of Batna 2, Batna, Algeria ' Department of Mathematics, University of Batna 2, Batna, Algeria

Abstract: We propose a primal-dual interior-point algorithm for linear optimisation based on a class of kernel functions which is eligible. New search directions and proximity measures are defined based on these functions. We derive the complexity bounds for large and small-update methods respectively. These are currently the best known complexity results for such methods.

Keywords: kernel function; linear optimisation; primal-dual interior-point methods; large-update methods.

DOI: 10.1504/IJMMNO.2019.098785

International Journal of Mathematical Modelling and Numerical Optimisation, 2019 Vol.9 No.2, pp.158 - 177

Received: 30 Oct 2017
Accepted: 16 Apr 2018
Published online: 02 Apr 2019 *

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