基于Greenberg-Pierskalla次微分的拟凸规划的KKT类最优性条件  

Karush-Kuhn-Tucker Type Optimality Conditions for Quasiconvex Programming in Terms of Greenberg-Pierskalla Subdifferentiation

作　　者：邱丽霞 方东辉[1] 王俊颖 QIU Lixia;FANG Donghui;WANG Junying(College of Mathematics and Statistics,Jishou University,Jishou 416000)

机构地区：[1]吉首大学数学与统计学院,吉首416000

出　　处：《系统科学与数学》2025年第2期554-562,共9页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金(12261037,11861033);湖南省自然科学基金(2024JJ7396)资助课题。

摘　　要：考虑目标函数和约束函数都是上半连续拟凸函数的拟凸优化问题,引入较文献(Suzuki,2021)弱的约束规范条件,刻画了该问题基于Greenberg-Pierskalla次微分的KKT类最优性条件,改进了前人的相关结论.In this paper,we introduce a weaker constraint qualification than that in reference(Suzuki,2021)and establish a Karush-Kuhn-Tucker type optimality condition for quasiconvex programming in terms of Greenberg-Pierskalla subdifferential when the objective function and the constraint functions are extended real-valued upper semi-continuous quasiconvex functions.

关 键 词：拟凸优化问题 约束规范条件 最优性条件 Greenberg-Pierskalla次微分 

分 类 号：O22[理学—运筹学与控制论]