An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application
In this paper, we propose a reptile search algorithm based on Lévy flight and interactive crossover strategy (LICRSA), and the improved algorithm is employed to improve the problems of poor convergence accuracy and slow iteration speed of the reptile search algorithm. First, the proposed algorithm i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/13/2329 |
| _version_ | 1827619389592043520 |
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| author | Liqiong Huang Yuanyuan Wang Yuxuan Guo Gang Hu |
| author_facet | Liqiong Huang Yuanyuan Wang Yuxuan Guo Gang Hu |
| author_sort | Liqiong Huang |
| collection | DOAJ |
| description | In this paper, we propose a reptile search algorithm based on Lévy flight and interactive crossover strategy (LICRSA), and the improved algorithm is employed to improve the problems of poor convergence accuracy and slow iteration speed of the reptile search algorithm. First, the proposed algorithm increases the variety and flexibility of the people by introducing the Lévy flight strategy to prevent premature convergence and improve the robustness of the population. Secondly, an iteration-based interactive crossover strategy is proposed, inspired by the crossover operator and the difference operator. This strategy is applied to the reptile search algorithm (RSA), and the convergence accuracy of the algorithm is significantly improved. Finally, the improved algorithm is extensively tested using 2 test sets: 23 benchmark test functions and 10 CEC2020 functions, and 5 complex mechanical engineering optimization problems. The numerical results show that LICRSA outperforms RSA in 15 (65%) and 10 (100%) of the 2 test sets, respectively. In addition, LICRSA performs best in 10 (43%) and 4 (40%) among all algorithms. Meanwhile, the enhanced algorithm shows superiority and stability in handling engineering optimization. |
| first_indexed | 2024-03-09T10:27:32Z |
| format | Article |
| id | doaj.art-c36f3726907143f4bc03fb26a8bf9a8e |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T10:27:32Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-c36f3726907143f4bc03fb26a8bf9a8e2023-12-01T21:35:38ZengMDPI AGMathematics2227-73902022-07-011013232910.3390/math10132329An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering ApplicationLiqiong Huang0Yuanyuan Wang1Yuxuan Guo2Gang Hu3College of Mathematics and Computer Application, Shangluo University, Shangluo 726000, ChinaElectronic Information and Electrical Engineering College, Shangluo University, Shangluo 726000, ChinaDepartment of Applied Mathematics, Xi’an University of Technology, Xi’an 710054, ChinaDepartment of Applied Mathematics, Xi’an University of Technology, Xi’an 710054, ChinaIn this paper, we propose a reptile search algorithm based on Lévy flight and interactive crossover strategy (LICRSA), and the improved algorithm is employed to improve the problems of poor convergence accuracy and slow iteration speed of the reptile search algorithm. First, the proposed algorithm increases the variety and flexibility of the people by introducing the Lévy flight strategy to prevent premature convergence and improve the robustness of the population. Secondly, an iteration-based interactive crossover strategy is proposed, inspired by the crossover operator and the difference operator. This strategy is applied to the reptile search algorithm (RSA), and the convergence accuracy of the algorithm is significantly improved. Finally, the improved algorithm is extensively tested using 2 test sets: 23 benchmark test functions and 10 CEC2020 functions, and 5 complex mechanical engineering optimization problems. The numerical results show that LICRSA outperforms RSA in 15 (65%) and 10 (100%) of the 2 test sets, respectively. In addition, LICRSA performs best in 10 (43%) and 4 (40%) among all algorithms. Meanwhile, the enhanced algorithm shows superiority and stability in handling engineering optimization.https://www.mdpi.com/2227-7390/10/13/2329reptile search algorithmLévy flightinteractive crossover strategybenchmarkengineering optimization |
| spellingShingle | Liqiong Huang Yuanyuan Wang Yuxuan Guo Gang Hu An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application Mathematics reptile search algorithm Lévy flight interactive crossover strategy benchmark engineering optimization |
| title | An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application |
| title_full | An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application |
| title_fullStr | An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application |
| title_full_unstemmed | An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application |
| title_short | An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application |
| title_sort | improved reptile search algorithm based on levy flight and interactive crossover strategy to engineering application |
| topic | reptile search algorithm Lévy flight interactive crossover strategy benchmark engineering optimization |
| url | https://www.mdpi.com/2227-7390/10/13/2329 |
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