$E$-凸函数的$E$-子微分及其在最小化问题中的应用

Pub Date : 2023-01-01 DOI:10.11650/tjm/230803
Tadeusz Antczak, Najeeb Abdulaleem
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引用次数: 0

摘要

本文定义了不可微(不一定)局部Lipschitz函数的子微分的新概念。即,对E$-凸函数引入了E$-次微分的概念和E$-次凸的概念。由此,引入了E$-次可微凸函数的概念,并研究了这类不可微非凸函数的一些性质。针对一类新的不可微优化问题,建立了相关函数的$E$-次微分项的最优性必要条件。利用引入的$E$-次凸性的概念,证明了所涉及的函数为$E$-次可微$E$-凸的不可微优化问题的上述必要最优性条件的充分性。
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$E$-subdifferential of $E$-convex Functions and its Applications to Minimization Problem
In this paper, a new concept of the subdifferential is defined for nondifferentiable (not necessarily) locally Lipschitz functions. Namely, the concept of $E$-subdifferential and the notion of $E$-subconvexity are introduced for $E$-convex functions. Thus, the notion of an $E$-subdifferentiable $E$-convex function is introduced and some properties of this class of nondifferentiable nonconvex functions are studied. The necessary optimality conditions in $E$-subdifferentials terms of the involved functions are established for a new class of nondifferentiable optimization problems. The introduced concept of $E$-subconvexity is used to prove the sufficiency of the aforesaid necessary optimality conditions for nondifferentiable optimization problems in which the involved functions are $E$-subdifferentiable $E$-convex.
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