Publication: A swarm-based artificial immune system for solving multimodal functions
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Date
2011
Authors
Yap D.F.W.
Koh S.P.
Tiong S.K.
Prajindra S.K.
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Abstract
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.
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Keywords
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)