Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization

Artificial immune system (AIS) is one of the natureinspired algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be improved further because the hypermutation in CSA itself c...

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Main Authors:	Yap, David F. W., Koh, S. P., Tiong, S. K.
Format:	Conference or Workshop Item
Published:	2011
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://www.icmlc.org/ http://www.icmlc.org/ http://eprints.utem.edu.my/3973/1/rp058_vol.4-C00778-001.pdf

id	utem-3973
recordtype	eprints
spelling	utem-39732015-05-28T02:38:56Z Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization Yap, David F. W. Koh, S. P. Tiong, S. K. TA Engineering (General). Civil engineering (General) Artificial immune system (AIS) is one of the natureinspired algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be improved further because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively,Genetic Algorithms (GAs) and Particle Swarm Optimization(PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. In this study, the CSA is modified using the best solution for each exposure (iteration) namely Single Best Remainder (SBR) CSA. In this study, the results show that the performance of the proposed algorithm (SBR-CSA) compares favourably with other algorithms while Half Best Insertion (HBI) CSA produced moderate results in most of the simulations. 2011 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utem.edu.my/3973/1/rp058_vol.4-C00778-001.pdf http://www.icmlc.org/ Yap, David F. W. and Koh, S. P. and Tiong, S. K. (2011) Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization. In: 3rd International Conference on Machine Learning and Computing (ICMLC 2011) , 26-28 Feb 2011, Singapore. http://eprints.utem.edu.my/3973/
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknikal Malaysia Melaka
building	UTeM Institutional Repository
collection	Online Access
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Yap, David F. W. Koh, S. P. Tiong, S. K. Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
description	Artificial immune system (AIS) is one of the natureinspired algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be improved further because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively,Genetic Algorithms (GAs) and Particle Swarm Optimization(PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. In this study, the CSA is modified using the best solution for each exposure (iteration) namely Single Best Remainder (SBR) CSA. In this study, the results show that the performance of the proposed algorithm (SBR-CSA) compares favourably with other algorithms while Half Best Insertion (HBI) CSA produced moderate results in most of the simulations.
format	Conference or Workshop Item
author	Yap, David F. W. Koh, S. P. Tiong, S. K.
author_facet	Yap, David F. W. Koh, S. P. Tiong, S. K.
author_sort	Yap, David F. W.
title	Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
title_short	Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
title_full	Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
title_fullStr	Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
title_full_unstemmed	Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
title_sort	antibody remainder method based artificial immune system for mathematical function optimization
publishDate	2011
url	http://www.icmlc.org/ http://www.icmlc.org/ http://eprints.utem.edu.my/3973/1/rp058_vol.4-C00778-001.pdf
first_indexed	2018-09-05T10:18:33Z
last_indexed	2018-09-05T10:18:33Z
_version_	1610762382442758144

Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization

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