Scalarizations and lagrange multipliers for approximat solutions in the vector optimization problems with set-valued maps

Ying Gao, Xinmin Yang, Jin Yang, Hong Yan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

Abstract

In this paper, we characterize approximate solutions of vector optimization problems with set-valued maps. We gives several characterizations of generalized subconvexlike set-valued functions(see [10]), which is a generalization of nearly subconvexlike functions introduced in [34]. We present alternative theorem and derived scalarization theorems for approximate solutions with generalized subconvexlike set-valued maps. And then, Lagrange multiplier theorems under generalized Slater constraint qualication are established.
Original languageEnglish
Pages (from-to)673-683
Number of pages11
JournalJournal of Industrial and Management Optimization
Volume11
Issue number2
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • Approximate solutions
  • Generalized subconvexlike
  • Lagrange multiplier theorems
  • Scalarizations
  • Set-valued maps
  • Vector optimization problems

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management
  • Control and Optimization
  • Applied Mathematics

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