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.

引用

页数：14

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