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Robust Necessary Optimality Conditions for Nondifferentiable Complex Fractional Programming with Uncertain Data

In this paper, we study robust necessary optimality conditions for a nondifferentiable complex fractional programming with uncertain data. A robust counterpart of uncertain complex fractional programming is introduced in the worst-case scenario. The concept of robust optimal solution of the uncertai...

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Detalles Bibliográficos
Autores principales: Chen, Jiawei, Al-Homidan, Suliman, Ansari, Qamrul Hasan, Li, Jun, Lv, Yibing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921289/
https://www.ncbi.nlm.nih.gov/pubmed/33678905
http://dx.doi.org/10.1007/s10957-021-01829-8
Descripción
Sumario:In this paper, we study robust necessary optimality conditions for a nondifferentiable complex fractional programming with uncertain data. A robust counterpart of uncertain complex fractional programming is introduced in the worst-case scenario. The concept of robust optimal solution of the uncertain complex fractional programming is introduced by using robust counterpart. We give an equivalence between the optimal solutions of the robust counterpart and a minimax nonfractional parametric programming. Finally, Fritz John-type and Karush–Kuhn–Tucker-type robust necessary optimality conditions of the uncertain complex fractional programming are established under some suitable conditions.