On nonsmooth robust multiobjective optimization under generalized convexity with applications to portfolio optimization
On nonsmooth robust multiobjective optimization under generalized convexity with applications to portfolio optimization
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DOI：
10.1016/j.ejor.2017.08.003
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发表时间：
2018-02-16
影响因子：
6.4
通讯作者：
Zafarani, Jafar
中科院分区：
文献类型：
--
作者：
Fakhar, Majid;Mahyarinia, Mohammad Reza;Zafarani, Jafar
对一类实值函数族引入了在给定点处广义凸的新概念，并推导出鲁棒（弱）有效解的非光滑最优性充分条件。此外，我们提出了一个不确定多目标优化问题的鲁棒对偶理论和Mond-Weir型对偶。在广义凸性假设下，得到了一些非光滑鞍点定理。最后，我们证明了我们的新概念的鲁棒优化和投资组合优化广义凸性的可行性。(C)2017 Elsevier B. V.版权所有。
We introduce a new concept of generalized convexity at a given point for a family of real-valued functions and deduce nonsmooth sufficient optimality conditions for robust (weakly) efficient solutions. In addition, we present a robust duality theory and Mond-Weir type duality for an uncertain multiobjective optimization problem. Furthermore, some nonsmooth saddle-point theorems are obtained under our generalized convexity assumption. Finally we show the viability of our new concept of generalized convexity for robust optimization and portfolio optimization. (C) 2017 Elsevier B.V. All rights reserved.