A swarm based artificial immune systems for solving multimodal functions

Artificial Immune Systems (AIS) have attracted enormous attention among researchers because the algorithms are able to improve global searching ability and efficiency. Nevertheless, the rate of convergence for AIS is relatively slow compared to other metaheuristic algorithms. On the other hand, gene...

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Main Authors: Yap, David F. W., Koh, S. P., Tiong, S. K., Prajindra, S. K.
Format: Article
Language:English
Published: Taylor & Francis 2011
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/3936/
http://eprints.utem.edu.my/id/eprint/3936/1/08839514.2011.606662.pdf
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author Yap, David F. W.
Koh, S. P.
Tiong, S. K.
Prajindra, S. K.
author_facet Yap, David F. W.
Koh, S. P.
Tiong, S. K.
Prajindra, S. K.
author_sort Yap, David F. W.
building UTeM Institutional Repository
collection Online Access
description Artificial Immune Systems (AIS) have attracted enormous attention among researchers because the algorithms are able to improve global searching ability and efficiency. Nevertheless, the rate of convergence for AIS is relatively slow compared to other metaheuristic algorithms. On the other hand, genetic algorithms (GAs) and particle swarm optimization (PSO) have been used successfully in solving optimization problems, although they tend to converge prematurely. Therefore, the good attributes of AIS and PSO are merged in order to reduce this limitation. It is observed that the proposed hybrid AIS (HAIS) achieved better performances in terms of convergence rate, accuracy, and stability against GA and AIS by comparing the optimization results of the mathematical functions. A similar result was achieved by HAIS in the engineering problem when compared to GA, PSO, and AIS.
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spelling utem-39362021-12-21T16:45:40Z http://eprints.utem.edu.my/id/eprint/3936/ A swarm based artificial immune systems for solving multimodal functions Yap, David F. W. Koh, S. P. Tiong, S. K. Prajindra, S. K. TA Engineering (General). Civil engineering (General) Artificial Immune Systems (AIS) have attracted enormous attention among researchers because the algorithms are able to improve global searching ability and efficiency. Nevertheless, the rate of convergence for AIS is relatively slow compared to other metaheuristic algorithms. On the other hand, genetic algorithms (GAs) and particle swarm optimization (PSO) have been used successfully in solving optimization problems, although they tend to converge prematurely. Therefore, the good attributes of AIS and PSO are merged in order to reduce this limitation. It is observed that the proposed hybrid AIS (HAIS) achieved better performances in terms of convergence rate, accuracy, and stability against GA and AIS by comparing the optimization results of the mathematical functions. A similar result was achieved by HAIS in the engineering problem when compared to GA, PSO, and AIS. Taylor & Francis 2011-10-09 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/3936/1/08839514.2011.606662.pdf Yap, David F. W. and Koh, S. P. and Tiong, S. K. and Prajindra, S. K. (2011) A swarm based artificial immune systems for solving multimodal functions. Applied Artificial Intelligence, 25 (8). pp. 693-707. ISSN 0883-9514 http://www.tandfonline.com/loi/uaai20 http://dx.doi.org/10.1080/08839514.2011.606662
spellingShingle TA Engineering (General). Civil engineering (General)
Yap, David F. W.
Koh, S. P.
Tiong, S. K.
Prajindra, S. K.
A swarm based artificial immune systems for solving multimodal functions
title A swarm based artificial immune systems for solving multimodal functions
title_full A swarm based artificial immune systems for solving multimodal functions
title_fullStr A swarm based artificial immune systems for solving multimodal functions
title_full_unstemmed A swarm based artificial immune systems for solving multimodal functions
title_short A swarm based artificial immune systems for solving multimodal functions
title_sort swarm based artificial immune systems for solving multimodal functions
topic TA Engineering (General). Civil engineering (General)
url http://eprints.utem.edu.my/id/eprint/3936/
http://eprints.utem.edu.my/id/eprint/3936/
http://eprints.utem.edu.my/id/eprint/3936/
http://eprints.utem.edu.my/id/eprint/3936/1/08839514.2011.606662.pdf