Robust Optimization with Data Driven Asymmetric Uncertainty Set Construction
نویسندگان
چکیده
In this paper, we introduced a novel method for asymmetric uncertainty set construction based on the distributional information of sampling data. Deterministic robust counterpart optimization formulation is derived for D-norm induced uncertainty set with the proposed method. Furthermore, the asymmetric set induced robust optimization model is compared with the classical symmetric set induced robust optimization model. A numerical example and a reactor design problem are investigated. The results demonstrate that using asymmetric uncertainty set leads to less conservative robust solution.
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