Abstract
This paper is devoted to the investigation of a class of uncertain multiobjective fractional semi-infinite optimization problems (\(UMFP \), for brevity). We first obtain, by combining robust optimization and scalarization methodologies, necessary and sufficient optimality conditions for robust approximate weakly efficient solutions of (\(UMFP \)). Then, we introduce a Mixed type approximate dual problem for (\(UMFP \)) and investigate their robust approximate duality relationships. Moreover, we obtain some robust approximate weak saddle point theorems for an uncertain multiobjective Lagrangian function related to (\(UMFP \)).
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Acknowledgements
The authors would like to thank the anonymous referees for valuable comments and suggestions, which helped to improve the paper
Funding
This research was supported by the Natural Science Foundation of Chongqing (cstc2020jcyj-msxmX0016), the ARC Discovery Grant (DP190103361), the Education Committee Project Foundation of Chongqing for Bayu Young Scholar, the Project of CTBU (ZDPTTD201908), and the Innovation Project of CTBU (yjscxx2021-112-58).
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Sun, X., Feng, X. & Teo, K.L. Robust optimality, duality and saddle points for multiobjective fractional semi-infinite optimization with uncertain data. Optim Lett 16, 1457–1476 (2022). https://doi.org/10.1007/s11590-021-01785-2
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DOI: https://doi.org/10.1007/s11590-021-01785-2