Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem
Joint Authors
Guo, Sha-Sha
Ma, Xiao-Xu
Wang, Jie-sheng
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-18
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The bat algorithm (BA) is a heuristic algorithm that globally optimizes by simulating the bat echolocation behavior.
In order to improve the search performance and further improve the convergence speed and optimization precision of the bat algorithm, an improved algorithm based on chaotic map is introduced, and the improved bat algorithm of Levy flight search strategy and contraction factor is proposed.
The optimal chaotic map operator is selected based on the simulation experiments results.
Then, a multipopulation parallel bat algorithm based on the island model is proposed.
Finally, the typical test functions are used to carry out the simulation experiments.
The simulation results show that the proposed improved algorithm can effectively improve the convergence speed and optimization accuracy.
American Psychological Association (APA)
Guo, Sha-Sha& Wang, Jie-sheng& Ma, Xiao-Xu. 2019. Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1129522
Modern Language Association (MLA)
Guo, Sha-Sha…[et al.]. Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1129522
American Medical Association (AMA)
Guo, Sha-Sha& Wang, Jie-sheng& Ma, Xiao-Xu. Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1129522
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1129522