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A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem

Lately, the field of Artificial Immune Systems (AIS) has attracted wide attention among researchers as the algorithm is able to improve local searching ability and efficiency. However, the rate of convergence for AIS is rather slow as compared to other Evolutionary Algorithms. Alternatively, Particl...

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Main Authors: Yap, D.F.W., Koh, S.P., Tiong, S.K., Prajindra, S.K.
Format: Article
Language:en_US
Published: 2017
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spelling my.uniten.dspace-59982018-01-03T03:43:27Z A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem Yap, D.F.W. Koh, S.P. Tiong, S.K. Prajindra, S.K. Lately, the field of Artificial Immune Systems (AIS) has attracted wide attention among researchers as the algorithm is able to improve local searching ability and efficiency. However, the rate of convergence for AIS is rather slow as compared to other Evolutionary Algorithms. Alternatively, Particle Swarm Optimization (PSO) has been used effectively in solving complicated optimization problems with simple coding and lesser parameters, but it tends to converge prematurely. Thus, the good features of AIS and PSO are combined in ordertoreduce their shortcomings. By comparing the optimization results of the mathematical functions and the engineering problem using hybrid AIS (HAIS) and AIS, it is observed that HAIS has better performances in terms of accuracy, convergence rate and stability. © Springer Science+Business Media B.V. 2011. 2017-12-08T07:49:36Z 2017-12-08T07:49:36Z 2012 Article 10.1007/s10462-011-9252-8 en_US Artificial Intelligence Review Volume 38, Issue 4, December 2012, Pages 291-301
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language en_US
description Lately, the field of Artificial Immune Systems (AIS) has attracted wide attention among researchers as the algorithm is able to improve local searching ability and efficiency. However, the rate of convergence for AIS is rather slow as compared to other Evolutionary Algorithms. Alternatively, Particle Swarm Optimization (PSO) has been used effectively in solving complicated optimization problems with simple coding and lesser parameters, but it tends to converge prematurely. Thus, the good features of AIS and PSO are combined in ordertoreduce their shortcomings. By comparing the optimization results of the mathematical functions and the engineering problem using hybrid AIS (HAIS) and AIS, it is observed that HAIS has better performances in terms of accuracy, convergence rate and stability. © Springer Science+Business Media B.V. 2011.
format Article
author Yap, D.F.W.
Koh, S.P.
Tiong, S.K.
Prajindra, S.K.
spellingShingle Yap, D.F.W.
Koh, S.P.
Tiong, S.K.
Prajindra, S.K.
A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem
author_facet Yap, D.F.W.
Koh, S.P.
Tiong, S.K.
Prajindra, S.K.
author_sort Yap, D.F.W.
title A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem
title_short A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem
title_full A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem
title_fullStr A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem
title_full_unstemmed A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem
title_sort hybrid artificial immune systems for multimodal function optimization and its application in engineering problem
publishDate 2017
_version_ 1644493818505986048
score 13.222552

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