Paper Info
Title
Infeasible interior-point method for symmetric optimization using a positive-asymptotic barrier.
Abstract
We propose a new primal-dual infeasible interior-point method for symmetric optimization by using Euclidean Jordan algebras. Different kinds of interior-point methods can be obtained by using search directions based on kernel functions. Some search directions can be also determined by applying an algebraic equivalent transformation on the centering equation of the central path. Using this method we introduce a new search direction, which can not be derived from a usual kernel function. For this reason, we use the new notion of positive-asymptotic kernel function which induces the class of corresponding barriers. In general, the main iterations of the infeasible interior-point methods are composed of one feasibility and several centering steps. We prove that in our algorithm it is enough to take only one centering step in a main iteration in order to obtain a well-defined algorithm. Moreover, we conclude that the algorithm finds solution in polynomial time and has the same complexity as the currently best known infeasible interior-point methods. Finally, we give some numerical results.
Year
DOI
Venue
2018
10.1007/s10589-018-0012-4
Comp. Opt. and Appl.
Keywords
Field
DocType
Symmetric optimization, Infeasible interior-point methods, Nesterov–Todd direction, Polynomial complexity
Equivalent transformation,Applied mathematics,Mathematical optimization,Algebraic number,Polynomial complexity,Euclidean geometry,Time complexity,Interior point method,Mathematics,Kernel (statistics)
Journal
Volume
Issue
ISSN
71
2
0926-6003
Citations 
PageRank 
References 
0
0.34
18
Authors
2
Name
Order
Citations
PageRank
Petra Renáta Rigó100.68
Zs. Darvay264.20