A swarm-based artificial immune system 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 D.F.W., Koh S.P., Tiong S.K., Prajindra S.K.
Other Authors: 22952562500
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Published: 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-295872023-12-28T15:05:43Z A swarm-based artificial immune system for solving multimodal functions Yap D.F.W. Koh S.P. Tiong S.K. Prajindra S.K. 22952562500 22951210700 15128307800 36053261400 Approximation theory Convergence of numerical methods Functions Genetic algorithms Immunology Artificial Immune System Convergence rates Engineering problems Global searching ability Mathematical functions Meta heuristic algorithm Multi modal function Optimization problems Rate of convergence Particle swarm optimization (PSO) 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. Copyright � 2011 Taylor & Francis Group, LLC. Final 2023-12-28T07:05:43Z 2023-12-28T07:05:43Z 2011 Article 10.1080/08839514.2011.606662 2-s2.0-80053075801 https://www.scopus.com/inward/record.uri?eid=2-s2.0-80053075801&doi=10.1080%2f08839514.2011.606662&partnerID=40&md5=8e666b07b70298ee1f3a2212103c44e6 https://irepository.uniten.edu.my/handle/123456789/29587 25 8 693 707 All Open Access; Bronze Open Access 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 Approximation theory
Convergence of numerical methods
Functions
Genetic algorithms
Immunology
Artificial Immune System
Convergence rates
Engineering problems
Global searching ability
Mathematical functions
Meta heuristic algorithm
Multi modal function
Optimization problems
Rate of convergence
Particle swarm optimization (PSO)
spellingShingle Approximation theory
Convergence of numerical methods
Functions
Genetic algorithms
Immunology
Artificial Immune System
Convergence rates
Engineering problems
Global searching ability
Mathematical functions
Meta heuristic algorithm
Multi modal function
Optimization problems
Rate of convergence
Particle swarm optimization (PSO)
Yap D.F.W.
Koh S.P.
Tiong S.K.
Prajindra S.K.
A swarm-based artificial immune system for solving multimodal functions
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. Copyright � 2011 Taylor & Francis Group, LLC.
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 swarm-based artificial immune system for solving multimodal functions
title_short A swarm-based artificial immune system for solving multimodal functions
title_full A swarm-based artificial immune system for solving multimodal functions
title_fullStr A swarm-based artificial immune system for solving multimodal functions
title_full_unstemmed A swarm-based artificial immune system for solving multimodal functions
title_sort swarm-based artificial immune system for solving multimodal functions
publishDate 2023
_version_ 1806427573193801728