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

共 50 条

[21] A Hybrid Glowworm Swarm Optimization Algorithm for Constrained Engineering Design Problems
Zhou, Yongquan
Zhou, Guo
Zhang, Junli
APPLIED MATHEMATICS & INFORMATION SCIENCES, 2013, 7 (01): : 379 - 388
[22] EABOA: Enhanced adaptive butterfly optimization algorithm for numerical optimization and engineering design problems
He, Kai
Zhang, Yong
Wang, Yu-Kun
Zhou, Rong-He
Zhang, Hong-Zhi
ALEXANDRIA ENGINEERING JOURNAL, 2024, 87 : 543 - 573
[23] White Shark Optimizer: A novel bio-inspired meta-heuristic algorithm for global optimization problems
Braik, Malik
Hammouri, Abdelaziz
Atwan, Jaffar
Al-Betar, Mohammed Azmi A.
Awadallah, Mohammed A.
KNOWLEDGE-BASED SYSTEMS, 2022, 243
[24] A MODIFIED FIREFLY ALGORITHM FOR ENGINEERING DESIGN OPTIMIZATION PROBLEMS
Kazemzadeh-Parsi, M. J.
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF MECHANICAL ENGINEERING, 2014, 38 (M2) : 403 - 421
[25] Optical microscope algorithm: A new metaheuristic inspired by microscope magnification for solving engineering optimization problems
Cheng, Min-Yuan
Sholeh, Moh Nur
KNOWLEDGE-BASED SYSTEMS, 2023, 279
[26] African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems
Abdollahzadeh, Benyamin
Gharehchopogh, Farhad Soleimanian
Mirjalili, Seyedali
COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 158
[27] Moth search algorithm: a bio-inspired metaheuristic algorithm for global optimization problems
Wang, Gai-Ge
MEMETIC COMPUTING, 2018, 10 (02) : 151 - 164
[28] Orca predation algorithm: A novel bio-inspired algorithm for global optimization problems
Jiang, Yuxin
Wu, Qing
Zhu, Shenke
Zhang, Luke
EXPERT SYSTEMS WITH APPLICATIONS, 2022, 188
[29] A multi-strategy improved slime mould algorithm for global optimization and engineering design problems
Deng, Lingyun
Liu, Sanyang
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2023, 404
[30] Modified prairie dog optimization algorithm for global optimization and constrained engineering problems
Yu, Huangjing
Wang, Yuhao
Jia, Heming
Abualigah, Laith
MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2023, 20 (11) : 19086 - 19132

← 1 2 3 4 5 →