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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.
Other Authors: 22952562500
Format: Article
Published: 2023
Subjects:
Artificial immune system
Diversity
Engineering problem
Optimization
Particle swarm optimization
Approximation theory
Functions
Particle swarm optimization (PSO)
Artificial Immune System
Convergence rates
Engineering problems
Local searching
Mathematical functions
Multimodal function optimization
Optimization problems
Rate of convergence
Problem solving
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spelling my.uniten.dspace-295402023-12-28T14:30:27Z 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. 22952562500 22951210700 15128307800 36053261400 Artificial immune system Diversity Engineering problem Optimization Particle swarm optimization Approximation theory Functions Optimization Particle swarm optimization (PSO) Artificial Immune System Convergence rates Diversity Engineering problems Local searching Mathematical functions Multimodal function optimization Optimization problems Rate of convergence Problem solving 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. Final 2023-12-28T06:30:27Z 2023-12-28T06:30:27Z 2012 Article 10.1007/s10462-011-9252-8 2-s2.0-84870238348 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870238348&doi=10.1007%2fs10462-011-9252-8&partnerID=40&md5=4db0a037b794be90e5e11ed221775392 https://irepository.uniten.edu.my/handle/123456789/29540 38 4 291 301 Scopus
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/
topic Artificial immune system
Diversity
Engineering problem
Optimization
Particle swarm optimization
Approximation theory
Functions
Optimization
Particle swarm optimization (PSO)
Artificial Immune System
Convergence rates
Diversity
Engineering problems
Local searching
Mathematical functions
Multimodal function optimization
Optimization problems
Rate of convergence
Problem solving
spellingShingle Artificial immune system
Diversity
Engineering problem
Optimization
Particle swarm optimization
Approximation theory
Functions
Optimization
Particle swarm optimization (PSO)
Artificial Immune System
Convergence rates
Diversity
Engineering problems
Local searching
Mathematical functions
Multimodal function optimization
Optimization problems
Rate of convergence
Problem solving
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
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.
author2 22952562500
author_facet 22952562500
Yap D.F.W.
Koh S.P.
Tiong S.K.
Prajindra S.K.
format Article
author 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 2023
_version_ 1806428510344970240
score 13.222552

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