Global convergence of a robust smoothing SQP method for semi-infinite programming

C. Ling, Liqun Qi, G. L. Zhou, S. Y. Wu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

The semi-infinite programming (SIP) problem is a program with infinitely many constraints. It can be reformulated as a nonsmooth nonlinear programming problem with finite constraints by using an integral function. Due to the nondifferentiability of the integral function, gradient-based algorithms cannot be used to solve this nonsmooth nonlinear programming problem. To overcome this difficulty, we present a robust smoothing sequential quadratic programming (SQP) algorithm for solving the nonsmooth nonlinear programming problem. At each iteration of the algorthm, we need to solve only a quadratic program that is always feasible and solvable. The global convergence of the algorithm is established under mild conditions. Numerical results are given.
Original languageEnglish
Pages (from-to)147-164
Number of pages18
JournalJournal of Optimization Theory and Applications
Volume129
Issue number1
DOIs
Publication statusPublished - 1 Apr 2006
Externally publishedYes

Keywords

  • Global convergence
  • Integral functions
  • Semi-infinite programming
  • Smoothing SQP algorithm

ASJC Scopus subject areas

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

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