Mathematical function optimization using AIS antibody remainder method

Yap, David F. W. and Koh, S. P. and Tiong, S. K. (2011) Mathematical function optimization using AIS antibody remainder method. International Journal of Machine Learning and Computing, 1 (1). pp. 13-19. ISSN 2010-3700

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Abstract

Artificial immune system (AIS) is one of the metaheuristics used for solving combinatorial optimization problems. In AIS, clonal selection algorithm (CSA) has good global searching capability. 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 solutions for each exposure (iteration) namely Single Best Remainder (SBR) - CSA. The results show that the proposed algorithm is able to improve the conventional CSA in terms of accuracy and stability for single and multi objective functions.

Item Type:	Article
Uncontrolled Keywords:	clonal selection, antibody, antigen, affinity maturation, mutation
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Electronics and Computer Engineering > Department of Telecommunication Engineering
Depositing User:	Dr David Yap
Date Deposited:	10 Jul 2012 01:26
Last Modified:	21 Dec 2021 16:02
URI:	http://eprints.utem.edu.my/id/eprint/3932
Statistic Details:	View Download Statistic

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