Characterizations of robust optimality conditions via image space analysis

Q. H. Ansari*, P. K. Sharma, X. Qin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

In this paper, we consider general scalar robust optimization problems and study the characterizations for optimality conditions in the general vector spaces where we do not require any topology on the considered space. By using the image space analysis and nonlinear separation function, we derive some necessary and sufficient optimality conditions, especially saddle point sufficient optimality conditions for scalar robust optimization problems. Moreover, we discuss the validity and effectiveness of our results for the shortest path problem.

Original languageEnglish
Pages (from-to)2063-2083
Number of pages21
JournalOptimization
Volume69
Issue number9
DOIs
StatePublished - 1 Sep 2020

Bibliographical note

Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • 90C30
  • 90C31
  • 90C46
  • Robust optimality conditions
  • image space analysis
  • nonlinear scalarization
  • shortest path problem
  • uncertain optimization

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Characterizations of robust optimality conditions via image space analysis'. Together they form a unique fingerprint.

Cite this