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

Jein Shan Chen*, Shaohua Pan

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

29 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
頁(從 - 到)581-606
頁數26
期刊Computational Optimization and Applications
45
發行號3
DOIs
出版狀態已發佈 - 2010 4月

ASJC Scopus subject areas

  • 控制和優化
  • 計算數學
  • 應用數學

指紋

深入研究「A one-parametric class of merit functions for the second-order cone complementarity problem」主題。共同形成了獨特的指紋。

引用此