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A Novel Quantum-Behaved Bat Algorithm with Mean Best Position Directed for Numerical Optimization
Joint Authors
Zhu, Binglian
Zhu, Wenyong
Liu, Zijuan
Duan, Qingyan
Cao, Long
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-18
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
This paper proposes a novel quantum-behaved bat algorithm with the direction of mean best position (QMBA).
In QMBA, the position of each bat is mainly updated by the current optimal solution in the early stage of searching and in the late search it also depends on the mean best position which can enhance the convergence speed of the algorithm.
During the process of searching, quantum behavior of bats is introduced which is beneficial to jump out of local optimal solution and make the quantum-behaved bats not easily fall into local optimal solution, and it has better ability to adapt complex environment.
Meanwhile, QMBA makes good use of statistical information of best position which bats had experienced to generate better quality solutions.
This approach not only inherits the characteristic of quick convergence, simplicity, and easy implementation of original bat algorithm, but also increases the diversity of population and improves the accuracy of solution.
Twenty-four benchmark test functions are tested and compared with other variant bat algorithms for numerical optimization the simulation results show that this approach is simple and efficient and can achieve a more accurate solution.
American Psychological Association (APA)
Zhu, Binglian& Zhu, Wenyong& Liu, Zijuan& Duan, Qingyan& Cao, Long. 2016. A Novel Quantum-Behaved Bat Algorithm with Mean Best Position Directed for Numerical Optimization. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-17.
https://search.emarefa.net/detail/BIM-1099720
Modern Language Association (MLA)
Zhu, Binglian…[et al.]. A Novel Quantum-Behaved Bat Algorithm with Mean Best Position Directed for Numerical Optimization. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-17.
https://search.emarefa.net/detail/BIM-1099720
American Medical Association (AMA)
Zhu, Binglian& Zhu, Wenyong& Liu, Zijuan& Duan, Qingyan& Cao, Long. A Novel Quantum-Behaved Bat Algorithm with Mean Best Position Directed for Numerical Optimization. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-17.
https://search.emarefa.net/detail/BIM-1099720
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099720