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The Frequency Assignment Problem (FAP) is one of the key issues in the design of GSM networks (Global System for Mobile communications), and will remain important in the foreseeable future. There are many versions of FAP, most of them benchmarking-like problems. We use a formulation of FAP, developed in published work, that focuses on aspects which are relevant for real-world GSM networks. In this paper, we have designed, adapted, and evaluated several types of metaheuristic for different time ranges. After a detailed statistical study, results indicate that these metaheuristics are very appropriate for this FAP. New interference results have been obtained, that significantly improve those published in previous research.

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Nowadays, mobile communications are experiencing a strong growth, being more and more indispensable. One of the key issues in the design of mobile networks is the Frequency Assignment Problem (FAP). This problem is crucial at present and will remain important in the foreseeable future. Real world instances of FAP typically involve very large networks, which can only be handled by heuristic methods. In the present work, we are interested in optimizing frequency assignments for problems described in a mathematical formalism that incorporates actual interference information, measured directly on the field, as is done in current GSM networks. To achieve this goal, a range of metaheuristics have been designed, adapted, and rigourously compared on two actual GSM networks modeled according to the latter formalism. In order to generate quickly and reliably high quality solutions, all metaheuristics combine their global search capabilities with a local-search method specially tailored for this domain. The experiments and statistical tests show that in general, all metaheuristics are able to improve upon results published in previous studies, but two of the metaheuristics emerge as the best performers: a populationFrancisco Luna, Antonio J. Nebro, and Enrique Alba Universidad de Málaga, Spain E-mail: {flv, antonio, eat}@lcc.uma.es César Estébanez, Ricardo Aler, and José M. Valls Universidad Carlos III de Madrid, Spain E-mail: {cesteban, aler, jvalls}@inf.uc3m.es Coromoto León, Carlos Segura, and Gara Miranda Universidad de La Laguna, Spain E-mail: {cleon, csegura, gmiranda}@ull.es José M. Chaves-González, Miguel A. Vega-Rodríguez, and Juan A. Gómez-Pulido Universidad de Extremadura, Spain E-mail: {jm, mavega, jangomez}@unex.es based algorithm (Scatter Search) and a trajectory based (1+1) Evolutionary Algorithm. Finally, the analysis of the frequency plans obtained offers insight about how the interference cost is reduced in the optimal plans.