Robustness in nonsmooth nonlinear multi-objective programming

M. Zamani, M. Soleimani-Damaneh, A. Kabgani

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Recently Georgiev, Luc, and Pardalos (2013), [Robust aspects of solutions in deterministic multiple objective linear programming, European Journal of Operational Research, 229(1), 29–36] introduced the notion of robust efficient solutions for linear multi-objective optimization problems. In this paper, we extend this notion to nonlinear case. It is shown that, under the compactness of the feasible set or convexity, each robust efficient solution is a proper efficient solution. Some necessary and sufficient conditions for robustness, with respect to the tangent cone and the non-ascent directions, are proved. An optimization problem for calculating a robustness radius followed by a comparison between the newly-defined robustness notion and two existing ones is presented. Moreover, some alterations of objective functions preserving weak/proper/robust efficiency are studied.
Original languageEnglish
Pages (from-to)370-378
JournalEuropean Journal of Operational Research
Volume247
Issue number2
DOIs
Publication statusPublished - Dec 2015
Externally publishedYes

Keywords

  • multiple objective programming
  • robust solution
  • nonsmooth optimization
  • Clarke generalized gradient
  • proper efficiency

Fingerprint

Dive into the research topics of 'Robustness in nonsmooth nonlinear multi-objective programming'. Together they form a unique fingerprint.

Cite this