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Issue title: Applied Mathematics Related to Nonlinear Problems
Guest editors: Juan L.G. Guirao and Wei Gao
Article type: Research Article
Authors: Ji, Yinga; * | Ma, Ganga | Wei, Jua | Dai, Yemingb
Affiliations: [a] Business School, University of Shanghai for Science and Technology, Shanghai, China | [b] School of Mathematics and Statistics, Qingdao University, Qingdao, China
Correspondence: [*] Corresponding author. Ying Ji, Business School, University of Shanghai for Science and Technology, Shanghai 200093, China. E-mail: jiying_1981@126.com.
Abstract: The goal of this paper is going to present a hybrid approach to solve multi-criteria bilevel optimization models with uncertain parameters in the objective functions. In reality, the player can not provide the weights to the objectives exactly. Since to assert the correct weight for objective is difficult, ambiguity is often not absent in the weights given by the player. Therefore, each player (leader or follower) usually has to choose a weight of his objective from a given set. Then, we proposed a robust optimization approach to copy with this situation, where each player obtains his strategy by minimizing his worst-case weighted sum objective over the given weight region. We note that the worst-case implies the maximization of the weights. The corresponding reformulation is presented with the different choice of weights. By an application in supply chain optimization with the consideration of both supply and demand uncertainties, the usefulness of the proposed method is shown. The comparison with the existed approach is also presented.
Keywords: Uncertain multi-criteria programs, bilevel optimization, robust, Pareto, supply chain
DOI: 10.3233/JIFS-169351
Journal: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2999-3008, 2017
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