Abstract
This paper aims to investigate optimality conditions for a weakly Pareto solution to a robust multi-objective optimization problem with locally Lipschitzian data. We do this by using a minimax programming approach, namely, by establishing the necessary optimality condition for a (local) optimal solution to a robust minimax optimization problem under a suitable constraint qualification, we then employ it to arrive in the desired target. In addition, some duality results for both robust minimax optimization problems and robust multi-objective optimization problems are also provided.
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This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2019R1A2C1008672).
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Hong, Z., Bae, K.D. & Kim, D.S. Minimax programming as a tool for studying robust multi-objective optimization problems. Ann Oper Res 319, 1589–1606 (2022). https://doi.org/10.1007/s10479-021-04179-w
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DOI: https://doi.org/10.1007/s10479-021-04179-w
Keywords
- Multi-objective optimization
- Minimax programming
- Generalized convexity
- KKT optimality conditions
- Duality