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A Combined Genetic-neural Algorithm for Mobility Management

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Journal of Mathematical Modelling and Algorithms

Abstract

This work presented a new approach to solve the location management problem by using the location areas approach. A combination of Genetic Algorithm and Hopfield Neural Network is used to find the optimal configuration of location areas in a mobile network. Toward this end, the location areas configuration of the network is modeled so that the general condition of all the chromosomes of each population improves rapidly by the help of a Hopfield Neural Network. The Hopfield Neural Network is included in the Genetic Algorithm optimization process, to expedite its convergence, since the generic Genetic Algorithm is not fast enough. Simulation results are very promising and they lead to network configurations that are unexpected.

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  1. School of Information Technologies, The University of Sydney, Sydney, NSW, 2006, Australia

    Javid Taheri & Albert Y. Zomaya

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  1. Javid Taheri
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  2. Albert Y. Zomaya
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Correspondence to Javid Taheri.

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Taheri, J., Zomaya, A.Y. A Combined Genetic-neural Algorithm for Mobility Management. J Math Model Algor 6, 481–507 (2007). https://doi.org/10.1007/s10852-007-9066-5

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