A smoothing Newton algorithm based on a one-parametric class of smoothing functions for linear programming over symmetric cones

Xiao-Hong Liu () and Zheng-Hai Huang ()

Mathematical Methods of Operations Research, 2009, vol. 70, issue 2, 385-404

Abstract: In this paper, we introduce a one-parametric class of smoothing functions which contains the Fischer–Burmeister smoothing function and the CHKS smoothing function as special cases. Based on this class of smoothing functions, a smoothing Newton algorithm is extended to solve linear programming over symmetric cones. The global and local quadratic convergence results of the algorithm are established under suitable assumptions. The theory of Euclidean Jordan algebras is a basic tool in our analysis. Copyright Springer-Verlag 2009

Keywords: Linear programming; Symmetric cone; Euclidean Jordan algebra; Smoothing Newton algorithm; 90C05; 90C22; 90C25; 90C30 (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s00186-008-0274-1

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