An improved termite life cycle optimizer algorithm for global function optimization
The termite life cycle optimizer algorithm (TLCO) is a new bionic meta-heuristic algorithm that emulates the natural behavior of termites in their natural habitat. This work presents an improved TLCO (ITLCO) to increase the speed and accuracy of convergence. A novel strategy for worker generation is...
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| Format: | Article |
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PeerJ Inc.
2025-02-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-2671.pdf |
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| author | Yanjiao Wang Mengjiao Wei |
| author_facet | Yanjiao Wang Mengjiao Wei |
| author_sort | Yanjiao Wang |
| collection | DOAJ |
| description | The termite life cycle optimizer algorithm (TLCO) is a new bionic meta-heuristic algorithm that emulates the natural behavior of termites in their natural habitat. This work presents an improved TLCO (ITLCO) to increase the speed and accuracy of convergence. A novel strategy for worker generation is established to enhance communication between individuals in the worker population and termite population. This strategy would prevent the original worker generation strategy from effectively balancing algorithm convergence and population diversity to reduce the risk of the algorithm in reaching a local optimum. A novel soldier generation strategy is proposed, which incorporates a step factor that adheres to the principles of evolution to further enhance the algorithm’s convergence speed. Furthermore, a novel replacement update mechanism is executed when the new individual is of lower quality than the original individual. This mechanism ensures a balance between the convergence of the algorithm and the diversity of the population. The findings from CEC2013, CEC2019, and CEC2020 test sets indicate that ITLCO exhibits notable benefits regarding convergence speed, accuracy, and stability in comparison with the basic TLCO algorithm and the four most exceptional meta-heuristic algorithms thus far. |
| format | Article |
| id | doaj-art-c7d3b38304fa4840bcd24b11ca9fc898 |
| institution | DOAJ |
| issn | 2376-5992 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-c7d3b38304fa4840bcd24b11ca9fc8982025-08-20T02:43:55ZengPeerJ Inc.PeerJ Computer Science2376-59922025-02-0111e267110.7717/peerj-cs.2671An improved termite life cycle optimizer algorithm for global function optimizationYanjiao WangMengjiao WeiThe termite life cycle optimizer algorithm (TLCO) is a new bionic meta-heuristic algorithm that emulates the natural behavior of termites in their natural habitat. This work presents an improved TLCO (ITLCO) to increase the speed and accuracy of convergence. A novel strategy for worker generation is established to enhance communication between individuals in the worker population and termite population. This strategy would prevent the original worker generation strategy from effectively balancing algorithm convergence and population diversity to reduce the risk of the algorithm in reaching a local optimum. A novel soldier generation strategy is proposed, which incorporates a step factor that adheres to the principles of evolution to further enhance the algorithm’s convergence speed. Furthermore, a novel replacement update mechanism is executed when the new individual is of lower quality than the original individual. This mechanism ensures a balance between the convergence of the algorithm and the diversity of the population. The findings from CEC2013, CEC2019, and CEC2020 test sets indicate that ITLCO exhibits notable benefits regarding convergence speed, accuracy, and stability in comparison with the basic TLCO algorithm and the four most exceptional meta-heuristic algorithms thus far.https://peerj.com/articles/cs-2671.pdfTermite life cycle optimizer algorithmNovel generative strategyNovel replacement update mechanismAdaptive crossoverMetaheuristic algorithm. |
| spellingShingle | Yanjiao Wang Mengjiao Wei An improved termite life cycle optimizer algorithm for global function optimization PeerJ Computer Science Termite life cycle optimizer algorithm Novel generative strategy Novel replacement update mechanism Adaptive crossover Metaheuristic algorithm. |
| title | An improved termite life cycle optimizer algorithm for global function optimization |
| title_full | An improved termite life cycle optimizer algorithm for global function optimization |
| title_fullStr | An improved termite life cycle optimizer algorithm for global function optimization |
| title_full_unstemmed | An improved termite life cycle optimizer algorithm for global function optimization |
| title_short | An improved termite life cycle optimizer algorithm for global function optimization |
| title_sort | improved termite life cycle optimizer algorithm for global function optimization |
| topic | Termite life cycle optimizer algorithm Novel generative strategy Novel replacement update mechanism Adaptive crossover Metaheuristic algorithm. |
| url | https://peerj.com/articles/cs-2671.pdf |
| work_keys_str_mv | AT yanjiaowang animprovedtermitelifecycleoptimizeralgorithmforglobalfunctionoptimization AT mengjiaowei animprovedtermitelifecycleoptimizeralgorithmforglobalfunctionoptimization AT yanjiaowang improvedtermitelifecycleoptimizeralgorithmforglobalfunctionoptimization AT mengjiaowei improvedtermitelifecycleoptimizeralgorithmforglobalfunctionoptimization |