Optimality Conditions and Duality for a Class of Generalized Convex Interval-Valued Optimization Problems

被引：19
|
作者：
Guo, Yating [1 ]
Ye, Guoju [1 ]
Liu, Wei [1 ]
Zhao, Dafang [2 ]
Treanta, Savin [3 ]
机构：
[1] Hohai Univ, Coll Sci, Nanjing 210098, Peoples R China
[2] Hubei Normal Univ, Sch Math & Stat, Huangshi 435002, Hubei, Peoples R China
[3] Univ Politehn Bucuresti, Dept Appl Math, Bucharest 060042, Romania
来源：
MATHEMATICS | 2021年 / 9卷 / 22期
基金：
湖北省教育厅重点项目;
关键词：
gH-symmetrically derivative; optimality conditions; wolfe duality; symmetric pseudo-convexity; symmetric quasi-convexity; LINEAR-PROGRAMMING PROBLEMS; OBJECTIVE FUNCTION; COEFFICIENTS;
D O I：
10.3390/math9222979
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper is devoted to derive optimality conditions and duality theorems for interval-valued optimization problems based on gH-symmetrically derivative. Further, the concepts of symmetric pseudo-convexity and symmetric quasi-convexity for interval-valued functions are proposed to extend above optimization conditions. Examples are also presented to illustrate corresponding results.
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页数：14
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