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.
|Number of pages||12|
|Journal||Engineering Applications of Artificial Intelligence|
|Early online date||18 Mar 2022|
|Publication status||E-pub ahead of print - 18 Mar 2022|
Bibliographical noteFunding 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 ).
© 2022 Elsevier Ltd
- Termite queen algorithm
- Benchmarked functions
- Loss minimization
- Metaheuristic technique
- Engineering design problems