Title
A smoothing Levenberg–Marquardt algorithm for solving a class of stochastic linear complementarity problem
Abstract
In this paper, it is considered for a class of stochastic linear complementarity problems (SLCPs) with finitely many elements. A smoothing Levenberg–Marquardt algorithm is proposed for solving the SLCP. Under suitable conditions, the global convergence and local quadratic convergence of the proposed algorithm is given. Some numerical results are reported in this paper, which confirms the good theoretical properties of the proposed algorithm.
Year
DOI
Venue
2011
10.1016/j.amc.2010.10.049
Applied Mathematics and Computation
Keywords
Field
DocType
Stochastic linear complementarity problems,Smoothing Levenberg–Marquardt algorithm,Convergence analysis,Numerical results
Complementarity (molecular biology),Convergence (routing),Mathematical optimization,Smoothing,Rate of convergence,Linear complementarity problem,Mathematics,Levenberg–Marquardt algorithm
Journal
Volume
Issue
ISSN
217
9
0096-3003
Citations 
PageRank 
References 
3
0.42
12
Authors
2
Name
Order
Citations
PageRank
Yajun Xie1352.26
Changfeng Ma219729.63