Advertisement

An Experimental Comparison of Two Different Encoding Schemes for the Location of Base Stations in Cellular Networks

  • Carlos A. Brizuela
  • Everardo Gutiérrez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2611)

Abstract

This paper presents preliminary results on the comparison of binary and integer based representations for the Base Stations Location (BSL) problem. The simplest model of this problem, which is already NP-complete, is dealt with to compare also different crossover operators. Experimental results support the hypothesis that the integer based representation with a specific crossover operator outperforms the more traditional binary one for a very specific set of instances.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ansari, N., Hou, E.: Computational Intelligence for Optimization. Kluwer Academic Publishers, Boston (1997)Google Scholar
  2. 2.
    Ausiello, G., Crescenzi, P., Gambosi, G., Kann, V., Marchetti-Spaccamela, A., Protasi, M.: Complexity and Approximation-Combinatorial Optimization Problems and Their Approximability. Springer-Verlag, Berlin Heidelberg New York (1999)zbMATHGoogle Scholar
  3. 3.
    Bierwirth, C., Mattfeld, D. C., Kopfer, H.: On Permutation Representations for Scheduling Problems. In Proceedings of Parallel Problem Solving from Nature. Lecture Notes in Computer Science, Vol. 1141Springer-Verlag, Berlin Heidelberg New York (1996) 310–318Google Scholar
  4. 4.
    Calégari, P. R.: Parallelization of population-based evolutionary algorithms for combinatorial optimization problems. PhD thesis, number 2046. Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland (1999)Google Scholar
  5. 5.
    Galota, M., Glaβer, C., Reith, S., Vollmer, H.: A Polynomial-Time Approximation Scheme for Base Station Positioning in UMTS Networks. Technical Report, Universitat Wurzburg (2000)Google Scholar
  6. 6.
    Garey, M. R., Johnson, D. S.: Computers and Intractability: A Guide to the Theory of NP-completeness. W. H. Freeman, New York (1979)Google Scholar
  7. 7.
    Gen, M., Cheng, R.: Genetic Algorithms and Engineering Optimization. John Wiley & Sons, New York (2000)Google Scholar
  8. 8.
    Glaβer, C., Reith, S., Vollmer, H.: The Complexity of Base Station Positioning in Cellular Networks. ICALP Workshops 2000. Proceedings in Informatics, Vol. 8 (2000) 167–177Google Scholar
  9. 9.
    Hochbaum, D. (ed.): Approximation Algorithms for NP-Hard Problems. PWS Publishing Company, Boston (1997)Google Scholar
  10. 10.
    Krishnamachari, B., Wicker, S. B.: Experimental analysis of local search algorithms for optimal base station location. In Proceedings of International Conference on Evolutionary Computing for Computer, Communication, Control and Power. Chennai, India (2000)Google Scholar
  11. 11.
    Mathar, R., Niessen, T.: Optimum positioning of base stations for cellular radio networks. Wireless Networks, Vol. 6. John Wiley & Sons, New York (2000) 421–428Google Scholar
  12. 12.
    Merchant, A., Sengupta, B.: Assignment of Cells to Switches in PCS Networks. IEEE/ACM Transactions on Networking, Vol. 3 No. 5. IEEE Press (1995) 521–526CrossRefGoogle Scholar
  13. 13.
    Meunier, H., Talbi, E., Reininger, P.: A Multiobjective Genetic Algorithm for Radio Network Optimization. In Proceedings of the 2000 Congress on Evolutionary Computation CEC00 (2000) 317–324Google Scholar
  14. 14.
    Murphey, R. A., Pardalos, P., Resende, M. G. C.: Frequency Assignment Problem. In Du, D.-Z., Pardalos, P. M. (eds.). Handbook of Combinatorial Optimization. Kluwer Academic Publishers (1999) 295–377Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Carlos A. Brizuela
    • 1
  • Everardo Gutiérrez
    • 1
  1. 1.Computer Science DepartmentCICESE Research CenterEnsenadaMéxico

Personalised recommendations