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|Title:||A hybrid artificial immune systems for multimodal function optimization and its application in engineering problem||Authors:||Yap, D.F.W.
|Issue Date:||2012||Journal:||Artificial Intelligence Review Volume 38, Issue 4, December 2012, Pages 291-301||Abstract:||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.||DOI:||10.1007/s10462-011-9252-8|
|Appears in Collections:||COE Scholarly Publication|
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