Optimality conditions for fuzzy optimization problems under granular convexity concept

被引：17

作者：

Zhang, Jianke ^{[1
]}

Chen, Xiaoyi ^{[1
]}

Li, Lifeng ^{[1
]}

Ma, Xiaojue ^{[1
]}

机构：

[1] Xian Univ Posts & Telecommun, Sch Sci, Xian 710121, Peoples R China

来源：

FUZZY SETS AND SYSTEMS | 2022年 / 447卷

关键词：

Fuzzy optimization problems; Karush-Kuhn-Tucker optimality conditions; Horizontal membership function (HMF); Granular convexity; Granular differentiability; VECTOR OPTIMIZATION; INTERVAL; KKT;

D O I：

10.1016/j.fss.2022.01.004

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, under the condition of granular differentiation, we consider the fuzzy optimization problems with the general fuzzy function as the objective function. Firstly, we introduce the concept of granular convexity, and propose the properties of the granular convex fuzzy functions. Secondly, we present the Karush-Kuhn-Tucker type optimality conditions of the fuzzy relative optimal solution of more general fuzzy programming problems and some test examples. Finally, the relationships between a class of variational inequalities and the fuzzy optimization problems are established.(c) 2022 Elsevier B.V. All rights reserved.

引用

页码：54 / 75

页数：22

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