Journal
NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION
Volume 39, Issue 15, Pages 1705-1726Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/01630563.2018.1492938
Keywords
Euclidean Jordan algebra; positive-asymptotic kernel function; polynomial complexity; symmetric cone; symmetric optimization
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Funding
- Ministry of Research and Innovation, CNCS - UEFISCDI within PNCDI III [PN-III-P4-ID-PCE-2016-0190]
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We define a new interior-point method (IPM), which is suitable for solving symmetric optimization (SO) problems. The proposed algorithm is based on a new search direction. In order to obtain this direction, we apply the method of algebraically equivalent transformation on the centering equation of the central path. We prove that the associated barrier cannot be derived from a usual kernel function. Therefore, we introduce a new notion, namely the concept of the positive-asymptotic kernel function. We conclude that this algorithm solves the problem in polynomial time and has the same complexity as the best known IPMs for SO.
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