Abstract
The Location Management of a mobile network is a major problem nowadays. One of the most popular strategies used to solve this problem is the Reporting Cells. To configure a mobile network is necessary to indicate what cells of the network are going to operate as Reporting Cells (RC). The choice of these cells is not trivial because they affect directly to the cost of the mobile network. Hereby we present a parallel cooperative strategy of evolutionary algorithms to solve the RC problem. This method tries to solve the Location Management, placing optimally the RC in a mobile network, minimizing its cost. Due to the large amount of solutions that we can find, this problem is suitable for being solved with evolutionary strategies. Our work consists in the implementation of some evolutionary algorithms that obtain very good results working in a parallel way on a cluster.
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Rubio-Largo, Á., González-Álvarez, D.L., Vega-Rodríguez, M.A., Almeida-Luz, S.M., Gómez-Pulido, J.A., Sánchez-Pérez, J.M. (2010). A Parallel Cooperative Evolutionary Strategy for Solving the Reporting Cells Problem. In: Corchado, E., Novais, P., Analide, C., Sedano, J. (eds) Soft Computing Models in Industrial and Environmental Applications, 5th International Workshop (SOCO 2010). Advances in Intelligent and Soft Computing, vol 73. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13161-5_10
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DOI: https://doi.org/10.1007/978-3-642-13161-5_10
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