A least-square semismooth Newton method for the second-order cone complementarity problem

Shaohua Pan, Jein Shan Chen

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We present a nonlinear least-square formulation for the second-order cone complementarity problem based on the Fischer-Burmeister (FB) function and the plus function. This formulation has two-fold advantages. First, the operator involved in the over-determined system of equations inherits the favourable properties of the FB function for local convergence, for example, the (strong) semi-smoothness; second, the natural merit function of the over-determined system of equations share all the nice features of the class of merit functions fYF studied in [J.-S. Chen and P. Tseng, An unconstrained smooth minimization reformulation of the second-order cone complementarity problem, Math. Program. 104 (2005), pp. 293-327] for global convergence. We propose a semi-smooth Levenberg-Marquardt method to solve the arising over-determined system of equations, and establish the global and local convergence results. Among others, the superlinear (quadratic) rate of convergence is obtained under strict complementarity of the solution and a local error bound assumption, respectively. Numerical results verify the advantages of the least-square reformulation for difficult problems.

Original languageEnglish
Pages (from-to)1-22
Number of pages22
JournalOptimization Methods and Software
Volume26
Issue number1
DOIs
Publication statusPublished - 2011 Feb

Keywords

  • Fischer-Burmeister function
  • Levenberg-Marquardt method
  • second-order cone complementarity problem
  • semi-smooth

ASJC Scopus subject areas

  • Software
  • Control and Optimization
  • Applied Mathematics

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