NDLI: Hybrid Artificial Immune System-Genetic Algorithm optimization based on mathematical test functions

Content Provider	IEEE Xplore Digital Library
Author	Ali, M.O. Koh, S.P. Chong, K.H. Yap, D.F.W.
Copyright Year	2010
Description	Author affiliation: Department of Electronics and Communication Engineering, Universiti Teknikal Malaysia Melaka(UTeM), Hang Tuah Jaya,76100 Durian Tunggal, Malaysia (Yap, D.F.W.) \|\| Department of Electronics and Communication Engineering, Universiti Tenaga Nasional (UNITEN), 43009 Kajang, Selangor Darul Ehsan, Malaysia (Ali, M.O.; Koh, S.P.; Chong, K.H.)
Abstract	This paper demonstrates a hybrid between two optimization methods that are Artificial Immune System (AIS) and Genetic Algorithm (GA). The capability of overcoming the shortcomings of individual algorithms without losing their advantages makes the hybrid techniques superior to the stand-alone ones based on the dominant purpose of hybridization. The improvement of the results that enable to get it if GA and AIS work separately is the main objective of this hybrid. The hybrid includes two processes; firstly, AIS is the attraction among the researchers as the algorithm. This enables it to develop local searching ability and efficiency yet the convergence rate for AIS is preferably not precise compared to the GA. Secondly, a Genetic Algorithm is typically initializing population randomly. The last generation of AIS will be the input to the next process of the hybrid which is the GA in this hybrid AIS-GA. Hybrid makes GA enters the stage of standard solutions more rapidly and more accurate compared with GA initialized population at random. To differentiate between the results in terms of achieving the minimum value for these functions, eight mathematical test functions are being used to make comparison.
Starting Page	256
Ending Page	261
File Size	1389475
Page Count	6
File Format	PDF
ISBN	9781424486472
e-ISBN	9781424486489
DOI	10.1109/SCORED.2010.5704012
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-13
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic Algorithm (GA) optimization mathematical test functions Gallium Cloning Hybrid Hybrid power systems Artificial Immune System (AIS) Ellipsoids
Content Type	Text
Resource Type	Article

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