Abstract
In this work we describe the methodology and results obtained when grid computing is applied to resolve a real-world frequency assignment problem (FAP) in GSM networks. We havJose used a precise mathematical formulation for this problem, which was developed in previous work, where the frequency plans are evaluated using accurate interference information taken from a real GSM network. We propose here a newly approach which lies in the usage of several versions of the GRASP (Greedy Randomized Adaptive Search Procedure) metaheuristic working together over a grid environment. Our study was divided into two stages: In the first one, we fixed the parameters of different GRASP variants using the grid so that each version obtained the best results possible when solving the FAP; then, in the second step, we developed a master-slave model using the grid where the GRASP tuned versions worked together as a team of evolutionary algorithms. Results show us that this approach obtains very good frequency plans when solving a real-world FAP.
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Chaves-González, J.M., Hernando-Carnicero, R., Vega-Rodríguez, M.A., Gómez-Pulido, J.A., Sánchez-Pérez, J.M. (2009). Solving a Realistic FAP Using GRASP and Grid Computing. In: Abdennadher, N., Petcu, D. (eds) Advances in Grid and Pervasive Computing. GPC 2009. Lecture Notes in Computer Science, vol 5529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01671-4_8
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DOI: https://doi.org/10.1007/978-3-642-01671-4_8
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