NDLI: Research on float representation niche genetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Mingyi Cui
Copyright Year	2008
Description	Author affiliation: Sch. of Inf., Henan Univ. of Finance & Econ., Zhengzhou (Mingyi Cui)
Abstract	Niche had better performance in increasing the population diversity of genetic algorithm (GA), in improving local researching performance of it. So far, research results of relating to niche GA were all on binary representation, there was almost no on float representation genetic algorithm (FRGA). But in improving the performance of GA and extending GApsilas application, float representation is superior to other representation. This paper presents a float representation niche genetic algorithm (FRNGA). In the paper, the mechanism of FRNGA is researched by it. Dynamic process is analyzed by it on niche emerging and merging and disassociating in genetic operation. The method is explored by it. The results of its research and experiment indicate that the performance of FRNGA is reliable. The method is feasible.
Starting Page	2053
Ending Page	2058
File Size	112604
Page Count	6
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4594468
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Gallium Genetics Convergence Merging Distance measurement Optimization Genetic Algorithm Niche Float Representation
Content Type	Text
Resource Type	Article

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