The semismooth-related properties of a merit function and a descent method for the nonlinear complementarity problem

Jein Shan Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Citations (Scopus)

Abstract

This paper is a follow-up of the work [Chen, J.-S.: J. Optimiz. Theory Appl., Submitted for publication (2004)] where an NCP-function and a descent method were proposed for the nonlinear complementarity problem. An unconstrained reformulation was formulated due to a merit function based on the proposed NCP-function. We continue to explore properties of the merit function in this paper. In particular, we show that the gradient of the merit function is globally Lipschitz continuous which is important from computational aspect. Moreover, we show that the merit function is SC 1 function which means it is continuously differentiable and its gradient is semismooth. On the other hand, we provide an alternative proof, which uses the new properties of the merit function, for the convergence result of the descent method considered in [Chen, J.-S.: J. Optimiz. Theory Appl., Submitted for publication (2004)].

Original languageEnglish
Pages (from-to)565-580
Number of pages16
JournalJournal of Global Optimization
Volume36
Issue number4
DOIs
Publication statusPublished - 2006 Dec

Keywords

  • Complementarity
  • Descent method
  • Merit function
  • SC function
  • Semismooth function

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'The semismooth-related properties of a merit function and a descent method for the nonlinear complementarity problem'. Together they form a unique fingerprint.

Cite this