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An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-24
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms.
This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems.
A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted.
Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively.
Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented.
Three different search equations with distinctive characters are employed using predetermined search probabilities.
By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved.
The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms.
Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature.
American Psychological Association (APA)
Yurtkuran, Alkın& Emel, Erdal. 2015. An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099771
Modern Language Association (MLA)
Yurtkuran, Alkın& Emel, Erdal. An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1099771
American Medical Association (AMA)
Yurtkuran, Alkın& Emel, Erdal. An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch. Computational Intelligence and Neuroscience. 2015. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099771
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099771