Abstract
In this paper we study two different meta-heuristics to solve a real-word frequency assignment problem (FAP) in GSM networks. We have used a precise mathematical formulation in which the frequency plans are evaluated using accurate interference information coming from a real GSM network. We have developed an improved version of the scatter search (SS) algorithm in order to solve this problem. After accurately tuning this algorithm, it has been compared with a version fixed for the FAP problem of the population-based incremental learning (PBIL) algorithm. The results show that SS obtains better frequency plannings than PBIL for all the experiments performed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Wireless Intelligence (2006), http://www.wirelessintelligence.com
Aardal, K.I., van Hoesen, S.P.M., Koster, A.M.C.A., Mannino, C., Sassano, A.: Models and Solution Techniques for Frequency Assignment Problems. 4OR 1(4), 261–317 (2003)
Eisenblätter, A.: Frequency Assignment in GSM Networks: Models, Heuristics, and Lower Bounds. PhD thesis, Technische Universität Berlin (2001)
Mouly, M., Paulet, M.B.: The GSM System for Mobile Communications. Telecom Publishing (1992)
Luna, F., Blum, C., Alba, E., Nebro, A.J.: ACO vs EAs for Solving a Real-World Frequency Assignment Problem in GSM Networks. In: GECCO 2007, London, UK, pp. 94–101 (2007)
Walke, B.H.: Mobile Radio Networks: Networking, Protocols and Traffic Performance. Wiley, Chichester (2002)
Domínguez-González, D., Chaves-González, J.M., Vega-Rodríguez, M.A., Gómez-Pulido, J.A., Sánchez-Pérez, J.M.: Using PBIL for Solving a Real-World Frequency Assignment Problem in GSM Networks. In: Neves, J., Santos, M.F., Machado, J.M. (eds.) EPIA 2007. LNCS (LNAI), vol. 4874, pp. 207–218. Springer, Heidelberg (2007)
Martí, R., Laguna, M., Glover, F.: Principles of Scatter Search. European Journal of Operational Research 169, 359–372 (2006)
Laguna, M., Hossell, K.P., Martí, R.: Scatter Search: Methodology and Implementation in C. Kluwer Academic Publishers, Norwell (2002)
Baluja, S.: Population-based Incremental Learning: A Method for Integrating Genetic Search based Function Optimization and Competitive Learning. Technical Report CMU-CS-94-163, Carnegie Mellon University (1994)
Baluja, S., Caruana, R.: Removing the Genetics from the Standard Genetic Algorithm. In: Twelfth Int. Conference on Machine Learning, San Mateo, CA, USA, pp. 38–46 (1995)
Simon, M.K., Alouini, M.-S.: Digital Communication over Fading Channels: A Unified Approach to Performance Analysis. Wiley, Chichester (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chaves-González, J.M., Vega-Rodríguez, M.A., Domínguez-González, D., Gómez-Pulido, J.A., Sánchez-Pérez, J.M. (2008). SS vs PBIL to Solve a Real-World Frequency Assignment Problem in GSM Networks. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2008. Lecture Notes in Computer Science, vol 4974. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78761-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-540-78761-7_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78760-0
Online ISBN: 978-3-540-78761-7
eBook Packages: Computer ScienceComputer Science (R0)