Soft Computing

, Volume 15, Issue 5, pp 975–990 | Cite as

Optimization algorithms for large-scale real-world instances of the frequency assignment problem

  • Francisco Luna
  • César Estébanez
  • Coromoto León
  • José M. Chaves-González
  • Antonio J. Nebro
  • Ricardo AlerEmail author
  • Carlos Segura
  • Miguel A. Vega-Rodríguez
  • Enrique Alba
  • José M. Valls
  • Gara Miranda
  • Juan A. Gómez-Pulido
Original Paper


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 be handled only 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. 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 population-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.


Frequency assignment problem Large-scale real-world instances Metaheuristics Optimal design 



This work has been partially funded by the Spanish Ministry of Science and Innovation and FEDER under contract TIN2008-06491-C04-04 (the MSTAR project). J.M. Chaves-González is supported by the research grant PRE06003 from Junta de Extremadura (Spain). The work of Gara Miranda has been developed under grant FPU-AP2004-2290. Francisco Luna acknowledges support from the grant BES-2006-13075 funded by the Spanish government. The work of Carlos Segura was funded by grant FPU-AP2008-03213.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Francisco Luna
    • 1
  • César Estébanez
    • 2
  • Coromoto León
    • 3
  • José M. Chaves-González
    • 4
  • Antonio J. Nebro
    • 1
  • Ricardo Aler
    • 2
    Email author
  • Carlos Segura
    • 3
  • Miguel A. Vega-Rodríguez
    • 4
  • Enrique Alba
    • 1
  • José M. Valls
    • 2
  • Gara Miranda
    • 3
  • Juan A. Gómez-Pulido
    • 4
  1. 1.Universidad de MálagaMalagaSpain
  2. 2.Universidad Carlos III de MadridMadridSpain
  3. 3.Universidad de La LagunaTenerifeSpain
  4. 4.Universidad de ExtremaduraBadajozSpain

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