Calmness and exact penalization in vector optimization with cone constraints

X. X. Huang, K. L. Teo, Xiaoqi Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

In this paper, a (local) calmness condition of order α is introduced for a general vector optimization problem with cone constraints in infinite dimensional spaces. It is shown that the (local) calmness is equivalent to the (local) exact penalization of a vector-valued penalty function for the constrained vector optimization problem. Several necessary and sufficient conditions for the local calmness of order α are established. Finally, it is shown that the local calmness of order 1 implies the existence of normal Lagrange multipliers.
Original languageEnglish
Pages (from-to)47-67
Number of pages21
JournalComputational Optimization and Applications
Volume35
Issue number1
DOIs
Publication statusPublished - 1 Sep 2006

Keywords

  • Calmness
  • Efficient solution
  • Exact penalization
  • Normal Lagrange multiplier
  • Vector optimization with cone constraints
  • Weakly efficient solution

ASJC Scopus subject areas

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

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