Proposing an Improved Version of the Bat Algorithm
The bat algorithm is an example of meta-heuristic algorithms from the collective swarm intelligence, which is based on the echolocation behavior of bats. This algorithm preserves the diversity of the solution by using a frequency tuning method that can quickly and efficiently shift from exploration...
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Semnan University
2024-12-01
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| Series: | مجله مدل سازی در مهندسی |
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| Online Access: | https://modelling.semnan.ac.ir/article_9231_f53f8df7d8c6019904f583ee3b9d89ef.pdf |
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| _version_ | 1841527708379512832 |
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| author | Davar Giveki Javad Ebrahimi Maryam Sarshar |
| author_facet | Davar Giveki Javad Ebrahimi Maryam Sarshar |
| author_sort | Davar Giveki |
| collection | DOAJ |
| description | The bat algorithm is an example of meta-heuristic algorithms from the collective swarm intelligence, which is based on the echolocation behavior of bats. This algorithm preserves the diversity of the solution by using a frequency tuning method that can quickly and efficiently shift from exploration to exploitation. Therefore, when a fast and accurate solution is needed, this algorithm becomes an efficient optimizer for any application. Although the bat algorithm has many practical benefits, it also has some disadvantages. One of these disadvantages that reduces its efficiency is being trapped in the local optimum. To solve the mentioned problem in this research, the position and speed of the initial population is updated in three ways with different formulas, this makes the final answer of the problem not trapped in the local optimum and diversity occurs in the population. In this article, the performance of the improved bat algorithm on 11 sample objective functions has been investigated and compared with other similar algorithms, and finally the results show the superiority and accuracy of this algorithm compared to similar samples. |
| format | Article |
| id | doaj-art-c8d6c310862a4d0288c7a9230af99676 |
| institution | Kabale University |
| issn | 2008-4854 2783-2538 |
| language | fas |
| publishDate | 2024-12-01 |
| publisher | Semnan University |
| record_format | Article |
| series | مجله مدل سازی در مهندسی |
| spelling | doaj-art-c8d6c310862a4d0288c7a9230af996762025-01-15T08:17:35ZfasSemnan Universityمجله مدل سازی در مهندسی2008-48542783-25382024-12-01227926727910.22075/jme.2024.33011.26089231Proposing an Improved Version of the Bat AlgorithmDavar Giveki0Javad Ebrahimi1Maryam Sarshar2Department of Computer Engineering, Technical and Engineering Faculty of Malayer University, Malayer, IranDepartment of Electrical Engineering, Institute of Higher Education Afarinesh Alam Gostar Borujard, Borujard, IranDepartment of Computer Engineering, Institute of Higher Education Afarinesh Alam Gostar Borujard, Borujard, IranThe bat algorithm is an example of meta-heuristic algorithms from the collective swarm intelligence, which is based on the echolocation behavior of bats. This algorithm preserves the diversity of the solution by using a frequency tuning method that can quickly and efficiently shift from exploration to exploitation. Therefore, when a fast and accurate solution is needed, this algorithm becomes an efficient optimizer for any application. Although the bat algorithm has many practical benefits, it also has some disadvantages. One of these disadvantages that reduces its efficiency is being trapped in the local optimum. To solve the mentioned problem in this research, the position and speed of the initial population is updated in three ways with different formulas, this makes the final answer of the problem not trapped in the local optimum and diversity occurs in the population. In this article, the performance of the improved bat algorithm on 11 sample objective functions has been investigated and compared with other similar algorithms, and finally the results show the superiority and accuracy of this algorithm compared to similar samples.https://modelling.semnan.ac.ir/article_9231_f53f8df7d8c6019904f583ee3b9d89ef.pdfoptimizationswarm intelligencemeta-heuristic algorithmlocal optimumbat algorithm |
| spellingShingle | Davar Giveki Javad Ebrahimi Maryam Sarshar Proposing an Improved Version of the Bat Algorithm مجله مدل سازی در مهندسی optimization swarm intelligence meta-heuristic algorithm local optimum bat algorithm |
| title | Proposing an Improved Version of the Bat Algorithm |
| title_full | Proposing an Improved Version of the Bat Algorithm |
| title_fullStr | Proposing an Improved Version of the Bat Algorithm |
| title_full_unstemmed | Proposing an Improved Version of the Bat Algorithm |
| title_short | Proposing an Improved Version of the Bat Algorithm |
| title_sort | proposing an improved version of the bat algorithm |
| topic | optimization swarm intelligence meta-heuristic algorithm local optimum bat algorithm |
| url | https://modelling.semnan.ac.ir/article_9231_f53f8df7d8c6019904f583ee3b9d89ef.pdf |
| work_keys_str_mv | AT davargiveki proposinganimprovedversionofthebatalgorithm AT javadebrahimi proposinganimprovedversionofthebatalgorithm AT maryamsarshar proposinganimprovedversionofthebatalgorithm |