A one-parametric class of merit functions for the second-order cone complementarity problem

Jein Shan Chen, Shaohua Pan

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

We investigate a one-parametric class of merit functions for the second-order cone complementarity problem (SOCCP) which is closely related to the popular Fischer-Burmeister (FB) merit function and natural residual merit function. In fact, it will reduce to the FB merit function if the involved parameter τ equals 2, whereas as τ tends to zero, its limit will become a multiple of the natural residual merit function. In this paper, we show that this class of merit functions enjoys several favorable properties as the FB merit function holds, for example, the smoothness. These properties play an important role in the reformulation method of an unconstrained minimization or a nonsmooth system of equations for the SOCCP. Numerical results are reported for some convex second-order cone programs (SOCPs) by solving the unconstrained minimization reformulation of the KKT optimality conditions, which indicate that the FB merit function is not the best. For the sparse linear SOCPs, the merit function corresponding to τ=2.5 or 3 works better than the FB merit function, whereas for the dense convex SOCPs, the merit function with τ=0.1, 0.5 or 1.0 seems to have better numerical performance.

Original languageEnglish
Pages (from-to)581-606
Number of pages26
JournalComputational Optimization and Applications
Volume45
Issue number3
DOIs
Publication statusPublished - 2010 Apr 1

Keywords

  • Complementarity
  • Jordan product
  • Merit function
  • Second-order cone

ASJC Scopus subject areas

  • Control and Optimization
  • Computational Mathematics
  • Applied Mathematics

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