Probabilistic Analysis of Search Performance of Differential Evolution Algorithm in Low-Dimensional Case

被引：0

作者：

Wang, Congjiao ^{[1
]}

Wei, Yuhan ^{[2
]}

Hou, Yanlin ^{[3
]}

Wu, Wenjia ^{[1
,4
]}

Huang, Cong ^{[3
]}

Chen, Jing ^{[3
]}

机构：

[1] Shanghai Dianji Univ, Sch Elect Engn, Shanghai 201306, Peoples R China

[2] Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, Shanghai 200240, Peoples R China

[3] Shanghai Maritime Univ, Merchant Marine Coll, Shanghai 201306, Peoples R China

[4] Shanghai Dianji Univ, Sch Arts & Sci, Shanghai 201306, Peoples R China

来源：

WIRELESS COMMUNICATIONS & MOBILE COMPUTING | 2022年 / 2022卷

关键词：

GLOBAL OPTIMIZATION; PARAMETERS;

D O I：

10.1155/2022/3936999

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a method of establishing and analyzing the probability model of its mutation and crossoperation process for differential evolution (DE) algorithm is proposed; especially, the escape ability and further optimization ability of individuals trapped in the local optimal neighborhood are deduced in detail, and the characteristic curves of the influence of key parameters such as population size, scaling factor, and crossfactor on the search performance of the algorithm are obtained. It provides a theoretical reference for the application of the algorithm.

引用

页数：21

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