文献类型：期刊文献

英文题名：Lower-order smoothed objective penalty functions based on filling properties for constrained optimization problems

作者：Tang, Jiahui[1];Wang, Wei[1];Xu, Yifan[2]

机构：[1]East China Univ Sci & Technol, Dept Math, Shanghai, Peoples R China;[2]Fudan Univ, Sch Management, Shanghai, Peoples R China

年份：2022

卷号：71

期号：6

起止页码：1579

外文期刊名：OPTIMIZATION

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000570271900001)】；

基金：This work is supported by National Nature Science Foundation of China (Grant Number 71531005).

语种：英文

外文关键词：Constrained optimization; globally optimal solutions; locally optimal solutions; smoothed objective penalty functions; filling properties

摘要：In this article, a class of lower-order smoothed objective penalty functions is introduced to find locally optimal points for constrained optimization problems. The exactness of the new penalty functions is studied. Based on the current locally optimal points, a new class of penalty functions based on filling properties is proposed. This new penalty function can be used to find a better locally optimal point. The exactness and filling properties of this penalty function are proved in this paper. To do this, two algorithms are presented to find the locally and globally optimal points. Additionally, their convergence is proved under some mild conditions. Finally, numerical results are included to illustrate the applicability of the local and global optimization algorithms.