A semismooth Newton method for nonlinear symmetric cone programming

In this paper, we employ the projection operator to design a semismooth Newton algorithm for solving nonlinear symmetric cone programming (NSCP). The algorithm is computable from theoretical standpoint and is proved to be locally quadratically convergent without assuming strict complementarity of th...

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Veröffentlicht in:Mathematical methods of operations research (Heidelberg, Germany) Jg. 76; H. 2; S. 129 - 145
Hauptverfasser: Kong, Lingchen, Meng, Qingmin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer-Verlag 01.10.2012
Springer
Springer Nature B.V
Schlagworte:
Algebra
Algorithms
Business and Management
Calculus of Variations and Optimal Control; Optimization
Decomposition
Mathematical functions
Mathematical models
Mathematical programming
Mathematics
Mathematics and Statistics
Methods
Newton methods
Nonlinearity
Operations research
Operations Research/Decision Theory
Operators
Original Article
Programming
Projection
Studies
Nonlinear symmetric cone programming
90C30
Euclidean Jordan algebra
Quadratical convergence
Secondary: 26B05
Primary: 65K05
Semismooth Newton algorithm
ISSN:1432-2994, 1432-5217
Online-Zugang:Volltext
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Zusammenfassung:In this paper, we employ the projection operator to design a semismooth Newton algorithm for solving nonlinear symmetric cone programming (NSCP). The algorithm is computable from theoretical standpoint and is proved to be locally quadratically convergent without assuming strict complementarity of the solution to NSCP.
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ISSN:1432-2994
1432-5217
DOI:10.1007/s00186-012-0393-6