A large-update primal–dual interior-point algorithm for second-order cone optimization based on a new proximity function. (2nd July 2016)

• Record Type: Journal Article
• Authors: Fathi-Hafshejani, S.; Mansouri, H.; Peyghami, M. Reza
• Is Part Of: Optimization. Volume 65:Number 7(2016)
• Page Start: 1477
• Page End: 1496
• Publication Date: 2016-07-02
• Subjects: Second-order cone optimization problem -- primal–dual interior-point methods -- kernel function; Mathematical optimization -- Periodicals; 519.7
• DOI: 10.1080/02331934.2016.1147034
• Languages: English
• ISSNs: 0233-1934

Abstract

Abstract : In this paper, we propose a large-update primal–dual interior-point algorithm for second-order cone optimization (SOCO) based on a class of kernel functions consisting of a trigonometric barrier term. The algorithm starts from a strictly feasible point and generates a sequence of points converging to an optimal solution of the problem. Using a simple analysis, we show that the algorithm has worst case iteration complexity for large-update primal–dual interior point methods which coincides with the so far best-known iteration bound for SOCO.