A meta-inspired termite queen algorithm for global optimization and engineering design problems

被引：23

作者：

Chen, Peng ^{[1
]}

Zhou, Shihua ^{[1
]}

Zhang, Qiang ^{[1
,2
]}

Kasabov, Nikola ^{[3
,4
]}

机构：

[1] Dalian Univ, Key Lab Adv Design & Intelligent Comp, Minist Educ, Dalian 116622, Peoples R China

[2] Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China

[3] Auckland Univ Technol, Knowledge Engn & Discovery Res Inst, Auckland 1010, New Zealand

[4] Ulster Univ, Intelligent Syst Res Ctr, Coleraine BT52 1SA, North Ireland

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2022年 / 111卷

关键词：

Termite queen algorithm; Benchmarked functions; Loss minimization; Metaheuristic technique; Engineering design problems; DIFFERENTIAL EVOLUTION; SEARCH;

D O I：

10.1016/j.engappai.2022.104805

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a novel bio-inspired termite queen algorithm (TQA) to solve optimization problems by simulating the division of labor in termite populations under a queen's rule. TQA is benchmarked on a set of 23 functions to test its performance at solving global optimization problems, and applied to six real world engineering design problems to verify its reliability and effectiveness. Comparative simulation studies with other algorithms are conducted, from whose results it is observed that TQA satisfactorily solves global optimization problems and engineering design problems.

引用

页数：12

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