Domain decomposition of finite element models utilizing eight meta-heuristic algorithms: A comparative study

被引：9

作者：

Kaveh, A. ^{[1
]}

Seddighian, M. R. ^{[1
]}

机构：

[1] Iran Univ Sci & Technol, Sch Civil Engn, Tehran, Iran

来源：

MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES | 2022年 / 50卷 / 08期

关键词：

Graph theory; finite element method; optimization; meta-heuristic; k-median; clustering; domain decomposition; parallel processing; TOPOLOGY OPTIMIZATION; MEDIAN PROBLEM;

D O I：

10.1080/15397734.2020.1781655

中图分类号：

O3 [力学];

学科分类号：

08 ; 0801 ;

摘要：

In this paper, thek-median of a graph is used to decompose the domain (mesh) of the continuous two- and three-dimensional finite element models. The problem ofk-median is stated as an optimization problem and is solved by utilizing eight robust meta-heuristic algorithms. The Artificial Bee Colony algorithm (ABC), Cyclical Parthenogenesis algorithm (CPA), Cuckoo Search algorithm (CS), Teaching-Learning Based Optimization algorithm (TLBO), Tug of War Optimization algorithm (TWO), Water Evaporation Optimization algorithm (WEO), Ray Optimization algorithm (RO), and Vibrating Particles System algorithm (VPS) constitute the set of algorithms that are employed in the present study. In order to tune the parameters of the meta-heuristics, the Taguchi method is used. The efficiency and robustness of the algorithms are investigated through two- and three- dimensional finite element models. Communicated by Marat Z Dosaev.

引用

页码：2616 / 2634

页数：19

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