A Novel Selection Approach for Genetic Algorithms for Global Optimization of Multimodal Continuous Functions
Joint Authors
Almanjahie, Ibrahim M.
Ahmad, Ishfaq
Haq, Ehtasham-ul
Hussain, Abid
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-05
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Genetic algorithms (GAs) are stochastic-based heuristic search techniques that incorporate three primary operators: selection, crossover, and mutation.
These operators are supportive in obtaining the optimal solution for constrained optimization problems.
Each operator has its own benefits, but selection of chromosomes is one of the most essential operators for optimal performance of the algorithms.
In this paper, an improved genetic algorithm-based novel selection scheme, i.e., stairwise selection (SWS) is presented to handle the problems of exploration (population diversity) and exploitation (selection pressure).
For its global performance, we compared with several other selection schemes by using ten well-known benchmark functions under various dimensions.
For a close comparison, we also examined the significance of SWS based on the statistical results.
Chi-square goodness of fit test is also used to evaluate the overall performance of the selection process, i.e., mean difference between observed and expected number of offspring.
Hence, the overall empirical results along with graphical representation endorse that the SWS outperformed in terms of robustness, stability, and effectiveness other competitors through authentication of performance index (PI).
American Psychological Association (APA)
Haq, Ehtasham-ul& Ahmad, Ishfaq& Hussain, Abid& Almanjahie, Ibrahim M.. 2019. A Novel Selection Approach for Genetic Algorithms for Global Optimization of Multimodal Continuous Functions. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1129635
Modern Language Association (MLA)
Haq, Ehtasham-ul…[et al.]. A Novel Selection Approach for Genetic Algorithms for Global Optimization of Multimodal Continuous Functions. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1129635
American Medical Association (AMA)
Haq, Ehtasham-ul& Ahmad, Ishfaq& Hussain, Abid& Almanjahie, Ibrahim M.. A Novel Selection Approach for Genetic Algorithms for Global Optimization of Multimodal Continuous Functions. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1129635
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1129635