Smoothing nonlinear penalty functions for constrained optimization problems

Xiaoqi Yang, Z. Q. Meng, X. X. Huang, G. T.Y. Pong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)

Abstract

In this article, we discuss a nondifferentiable nonlinear penalty method for an optimization problem with inequality constraints. A smoothing method is proposed for the nonsmooth nonlinear penalty function. Error estimations are obtained among the optimal value of smoothed penalty problem, the optimal value of the nonsmooth nonlinear penalty optimization problem and that of the original constrained optimization problem. We give an algorithm for the constrained optimization problem based on the smoothed nonlinear penalty method and prove the convergence of the algorithm. The efficiency of the smoothed nonlinear penalty method is illustrated with a numerical example.
Original languageEnglish
Pages (from-to)351-364
Number of pages14
JournalNumerical Functional Analysis and Optimization
Volume24
Issue number3-4
DOIs
Publication statusPublished - 1 Jan 2003

Keywords

  • Constrained optimization
  • Nonlinear penalty function
  • Optimal solution
  • Smoothing method
  • ε-feasible solution

ASJC Scopus subject areas

  • Analysis
  • Signal Processing
  • Computer Science Applications
  • Control and Optimization

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