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A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search
Joint Authors
Villagra, Andrea
Leguizamón, Guillermo
Alba, Enrique
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-14
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This work presents the results of a new methodology for hybridizing metaheuristics.
By first locating the active components (parts) of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms.
This gives a concrete way of constructing new techniques that contrasts the spread ad hoc way of hybridizing.
In this paper, the enhanced algorithm is a Cellular Genetic Algorithm (cGA) which has been successfully used in the past to find solutions to such hard optimization problems.
In order to extend and corroborate the use of active components as an emerging hybridization methodology, we propose here the use of active components taken from Scatter Search (SS) to improve cGA.
The results obtained over a varied set of benchmarks are highly satisfactory in efficacy and efficiency when compared with a standard cGA.
Moreover, the proposed hybrid approach (i.e., cGA+SS) has shown encouraging results with regard to earlier applications of our methodology.
American Psychological Association (APA)
Villagra, Andrea& Alba, Enrique& Leguizamón, Guillermo. 2016. A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099785
Modern Language Association (MLA)
Villagra, Andrea…[et al.]. A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1099785
American Medical Association (AMA)
Villagra, Andrea& Alba, Enrique& Leguizamón, Guillermo. A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099785
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099785