Nonlinear Lagrange duality theorems and penalty function methods in continuous optimization

C. Y. Wang, Xiaoqi Yang, X. M. Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)

Abstract

We propose a general dual program for a constrained optimization problem via generalized nonlinear Lagrangian functions. Our dual program includes a class of general dual programs with explicit structures as special cases. Duality theorems with the zero duality gap are proved under very general assumptions and several important corollaries which include some known result are given. Using dual functions as penalty functions, we also establish that a sequence of approximate optimal solutions of the penalty function converges to the optimal solution of the original optimization problem.
Original languageEnglish
Pages (from-to)473-484
Number of pages12
JournalJournal of Global Optimization
Volume27
Issue number4
DOIs
Publication statusPublished - 1 Dec 2003

Keywords

  • ε-optimal solution
  • Dual program
  • Nonlinear Lagrangian function
  • Penalty function
  • Zero duality gap

ASJC Scopus subject areas

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

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