Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 270, Issue 1, Pages 40-50Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2018.03.018
Keywords
Robustness and sensitivity analysis; Multi-objective optimization; Convex optimization; Robust optimization; Robust efficient solutions
Funding
- Australian Research Council [DP120100467]
- MINECO of Spain
- ERDF of EU [MTM2014-59179-C2-1-P, ECO2016-77200-P]
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This paper deals with uncertain multi-objective convex programming problems, where the data of the objective function or the constraints or both are allowed to be uncertain within specified uncertainty sets. We present sufficient conditions for the existence of highly robust weakly efficient solutions, that is, robust feasible solutions which are weakly efficient for any possible instance of the objective function within a specified uncertainty set. This is done by way of estimating the radius of highly robust weak efficiency under linearly distributed uncertainty of the objective functions. In the particular case of robust quadratic multi-objective programs, we show that these sufficient conditions can be expressed in terms of the original data of the problem, extending and improving the corresponding results in the literature for robust multi-objective linear programs under ball uncertainty. (C) 2018 Elsevier B.V. All rights reserved.
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