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

Peng Chen; Shihua Zhou; Qiang  Zhang; Nikola Kasabov

doi:10.1016/j.engappai.2022.104805

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

Peng Chen, Shihua Zhou, Qiang Zhang, Nikola Kasabov

Research output: Contribution to journal › Article › peer-review

22 Citations (Scopus)

179 Downloads (Pure)

Abstract

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.

Original language	English
Article number	104805
Pages (from-to)	1-12
Number of pages	12
Journal	Engineering Applications of Artificial Intelligence
Volume	111
Early online date	18 Mar 2022
DOIs	https://doi.org/10.1016/j.engappai.2022.104805
Publication status	Published (in print/issue) - 31 May 2022

Bibliographical note

Funding Information:
This work is supported by the National Key R & D Program of China (No. 2018YFC0910 500 ), the National Natural Science Foundation of China (Nos. 61425002 , 61751203 , 61772100 , 61972266 , 61802040 , 61672121 , 61572093 ), Program for Changjiang Scholars and Innovative Research Team in University (No. IRT_15R07 ), the Program for Liaoning Innovative Research Team in University (No. LT2017012 ), the Natural Science Foundation of Liaoning Province (Nos. 20180551241 , 2019-ZD0567 ), the High-level Talent Innovation Support Program of Dalian City (Nos. 2017RQ060 , 2018RQ75 ), the Dalian Outstanding Young Science and Technology Talent Support Program (No. 2017RJ08 ), Scientific Research Fund of Liaoning Provincial Education Department, China (No. LJKZ1186 , JYT19051 ), Dalian University Scientific Research Platform Program (No. 202101YB02 ).

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

Termite queen algorithm
Benchmarked functions
Loss minimization
Metaheuristic technique
Engineering design problems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.engappai.2022.104805

JoJo queentermit accepted 2022Author Accepted Manuscript, 2.5 MBLicence: CC BY-NC-ND

Cite this

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abstract = "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.",

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AU - Kasabov, Nikola

N1 - Funding Information: This work is supported by the National Key R & D Program of China (No. 2018YFC0910 500 ), the National Natural Science Foundation of China (Nos. 61425002 , 61751203 , 61772100 , 61972266 , 61802040 , 61672121 , 61572093 ), Program for Changjiang Scholars and Innovative Research Team in University (No. IRT_15R07 ), the Program for Liaoning Innovative Research Team in University (No. LT2017012 ), the Natural Science Foundation of Liaoning Province (Nos. 20180551241 , 2019-ZD0567 ), the High-level Talent Innovation Support Program of Dalian City (Nos. 2017RQ060 , 2018RQ75 ), the Dalian Outstanding Young Science and Technology Talent Support Program (No. 2017RJ08 ), Scientific Research Fund of Liaoning Provincial Education Department, China (No. LJKZ1186 , JYT19051 ), Dalian University Scientific Research Platform Program (No. 202101YB02 ). Publisher Copyright: © 2022 Elsevier Ltd

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N2 - 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.

AB - 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.

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KW - Metaheuristic technique

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

Abstract

Bibliographical note

Keywords

UN SDGs

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