Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19656
Title: Sub-quadratic convergence of a smoothing Newton algorithm for the P 0 - And monotone LCP
Authors: Huang, ZH
Qi, L 
Sun, D
Keywords: Global convergence
Linear complementarity problem
Smoothing Newton method
Sub-quadratic convergence
Issue Date: 2004
Source: Mathematical programming, 2004, v. 99, no. 3, p. 423-441 How to cite?
Journal: Mathematical Programming 
Abstract: Given [InlineMediaObject not available: see fulltext.], the linear complementarity problem (LCP) is to find [InlineMediaObject not available: see fulltext.] such that (x, s) ≥ 0,s=Mx+q,x Ts =0. By using the Chen-Harker-Kanzow-Smale (CHKS) smoothing function, the LCP is reformulated as a system of parameterized smooth-nonsmooth equations. As a result, a smoothing Newton algorithm, which is a modified version of the Qi-Sun-Zhou algorithm [Mathematical Programming, Vol. 87, 2000, pp. 1-35], is proposed to solve the LCP with M being assumed to be a P 0 -matrix (P 0 -LCP). The proposed algorithm needs only to solve one system of linear equations and to do one line search at each iteration. It is proved in this paper that the proposed algorithm has the following convergence properties: (i) it is well-defined and any accumulation point of the iteration sequence is a solution of the P 0 -LCP; (ii) it generates a bounded sequence if the P 0 -LCP has a nonempty and bounded solution set; (iii) if an accumulation point of the iteration sequence satisfies a nonsingularity condition, which implies the P 0 -LCP has a unique solution, then the whole iteration sequence converges to this accumulation point sub-quadratically with a Q-rate 2-t, where t (0,1) is a parameter; and (iv) if M is positive semidefinite and an accumulation point of the iteration sequence satisfies a strict complementarity condition, then the whole sequence converges to the accumulation point quadratically.
URI: http://hdl.handle.net/10397/19656
ISSN: 0025-5610
DOI: 10.1007/s10107-003-0457-8
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