A Multistrategy Optimization Improved Artificial Bee Colony Algorithm
Author
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-03
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Being prone to the shortcomings of premature and slow convergence rate of artificial bee colony algorithm, an improved algorithm was proposed.
Chaotic reverse learning strategies were used to initialize swarm in order to improve the global search ability of the algorithm and keep the diversity of the algorithm; the similarity degree of individuals of the population was used to characterize the diversity of population; population diversity measure was set as an indicator to dynamically and adaptively adjust the nectar position; the premature and local convergence were avoided effectively; dual population search mechanism was introduced to the search stage of algorithm; the parallel search of dual population considerably improved the convergence rate.
Through simulation experiments of 10 standard testing functions and compared with other algorithms, the results showed that the improved algorithm had faster convergence rate and the capacity of jumping out of local optimum faster.
American Psychological Association (APA)
Liu, Wen. 2014. A Multistrategy Optimization Improved Artificial Bee Colony Algorithm. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1048392
Modern Language Association (MLA)
Liu, Wen. A Multistrategy Optimization Improved Artificial Bee Colony Algorithm. The Scientific World Journal No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1048392
American Medical Association (AMA)
Liu, Wen. A Multistrategy Optimization Improved Artificial Bee Colony Algorithm. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1048392
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048392