A Novel Hybrid Clonal Selection Algorithm with Combinatorial Recombination and Modified Hypermutation Operators for Global Optimization
Joint Authors
Zhang, Weiwei
Lin, Jingjing
Jing, Honglei
Zhang, Qiuwen
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-08
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Artificial immune system is one of the most recently introduced intelligence methods which was inspired by biological immune system.
Most immune system inspired algorithms are based on the clonal selection principle, known as clonal selection algorithms (CSAs).
When coping with complex optimization problems with the characteristics of multimodality, high dimension, rotation, and composition, the traditional CSAs often suffer from the premature convergence and unsatisfied accuracy.
To address these concerning issues, a recombination operator inspired by the biological combinatorial recombination is proposed at first.
The recombination operator could generate the promising candidate solution to enhance search ability of the CSA by fusing the information from random chosen parents.
Furthermore, a modified hypermutation operator is introduced to construct more promising and efficient candidate solutions.
A set of 16 common used benchmark functions are adopted to test the effectiveness and efficiency of the recombination and hypermutation operators.
The comparisons with classic CSA, CSA with recombination operator (RCSA), and CSA with recombination and modified hypermutation operator (RHCSA) demonstrate that the proposed algorithm significantly improves the performance of classic CSA.
Moreover, comparison with the state-of-the-art algorithms shows that the proposed algorithm is quite competitive.
American Psychological Association (APA)
Zhang, Weiwei& Lin, Jingjing& Jing, Honglei& Zhang, Qiuwen. 2016. A Novel Hybrid Clonal Selection Algorithm with Combinatorial Recombination and Modified Hypermutation Operators for Global Optimization. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1099724
Modern Language Association (MLA)
Zhang, Weiwei…[et al.]. A Novel Hybrid Clonal Selection Algorithm with Combinatorial Recombination and Modified Hypermutation Operators for Global Optimization. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1099724
American Medical Association (AMA)
Zhang, Weiwei& Lin, Jingjing& Jing, Honglei& Zhang, Qiuwen. A Novel Hybrid Clonal Selection Algorithm with Combinatorial Recombination and Modified Hypermutation Operators for Global Optimization. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1099724
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099724