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A Parameter-Free Genetic Algorithm for a Fixed Channel Assignment Problem with Limited Bandwidth

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Parallel Problem Solving from Nature — PPSN VII (PPSN 2002)

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Abstract

Increasing the channel re-usability is necessary for reducing the call-blocking rate in any cellular systems with limited bandwidth and a large number of subscribers. To increase the re-usability, we need an efficient channel assignment algorithm that minimizes the sum of blocking cost and interference cost. We propose a new genetic algorithm for the problem based on the parameter-free GA. The proposed GA finds a good sequence of codes for a virtual machine that produces channel assignment. Results are given which show that our GA, without tedious parameter tuning, produces far better solutions to several practical problems than the existing GAs.

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References

  1. Bean, J.C.: Genetics and random keys for sequencing and optimization, ORSA Journal of Computing, vol.6, no.2, pp.154–160 (1994).

    MATH  Google Scholar 

  2. Crompton, W., Hurley, S., and Stephens, N.M.: Applying genetic algorithms to frequency assignment problems, Proc. SPIE Conf. Neural and Stochastic Methods in Image and Signal Processing, vol.2304, pp.76–84 (1994).

    Google Scholar 

  3. Hurley, S., Smith, D.H., and Thiel, S.U.: FASoft: a system for discrete channel frequency assignment, Radio Science, vol.32, no.5, pp.1921–1939 (1997).

    Article  Google Scholar 

  4. Horng, J.T., Jin, M.H., and Kao, C.Y.: Solving fixed channel assignment problems by an evolutionary approach, Proc. of GECCO-2001, pp.351–358 (2001).

    Google Scholar 

  5. Jin, M.H., Wu, H.K., Horng, J.Z., and Tsai, C.H.: An evolutionary approach to fixed channel assignment problems with limited bandwidth constraint, Proc. of IEEE ICC 2001, vol.7, pp.2100–2104 (2001).

    Google Scholar 

  6. Kim, J.-S., Park, S.H., Dowd, P.W., and Nasrabadi, N.M.: Comparison of two optimization techniques for channel assignment in cellular radio network, Proc. of IEEE Int. Conf. Commun., vol.3, pp.850–1854 (1995).

    Google Scholar 

  7. Kizu, S., Sawai, H., and Endo, H.: Parameter-free genetic algorithm: GA without setting genetic parameters, Proc. of 1997 International Symposium on Nonlinear Theory and its Application, vol.2 of 2, pp.1273–1276 (1997).

    Google Scholar 

  8. Matsui, S. and Tokoro, K.: A new genetic algorithm for minimum span frequency assignment using permutation and clique, Proc. of GECCO-2000, pp.682–689 (2000).

    Google Scholar 

  9. Matsui, S. and Tokoro, K.: Improving the performance of a genetic algorithm for minimum span frequency assignment problem with an adaptive mutation rate and a new initialization method, Proc. of GECCO-2001, pp.1359–1366 (2001).

    Google Scholar 

  10. Ngo, C.Y. and Li, V.O.K.: Fixed channel assignment in cellular radio networks using a modified genetic algorithm, IEEE Trans. Veh. Technol., vol.47, no.1, pp.163–172 (1998).

    Article  Google Scholar 

  11. Rothlauf, F., Goldberg, D.E., and Heinzl, A.: Bad coding and the utility of welldesigned genetic algorithms, Proc. of GECCO-2000, pp.355–362 (2000).

    Google Scholar 

  12. Sawai, H., Kizu, S.: Parameter-free genetic algorithm inspired by “disparity theory of evolution,” Proc. of PPSN-V, pp.702–711 (1998).

    Google Scholar 

  13. Smith, D.H., Hurley, S., and Thiel, S.U.: Improving heuristics for the frequency assignment problem, Eur. J. Oper. Res., vol.107, no.1, pp.76–86 (1998).

    Article  MATH  Google Scholar 

  14. Valenzuela, C., Hurley, S., and Smith, D.: A permutation based algorithm for minimum span frequency assignment, Proc. of PPSN-V, pp.907–916 (1998).

    Google Scholar 

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Authors and Affiliations

  1. Communication & Information Research Laboratory (CIRL), Central Research Institute of Electric Power Industry (CRIEPI), 2-11-1 Iwado-kita, Komae-shi, 201-8511, Tokyo, Japan

    Shouichi Matsui, Isamu Watanabe & Ken-ichi Tokoro

Authors
  1. Shouichi Matsui
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  2. Isamu Watanabe
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  3. Ken-ichi Tokoro
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Editor information

Editors and Affiliations

  1. Escuela Técnica Superior de Ingeniería Informática, 18071, Granada, Spain

    Juan Julián Merelo Guervós

  2. Department of Informatics, Technological Educational Institute of Thessaloniki, 54101, Thessaloniki, Greece

    Panagiotis Adamidis

  3. Department of Informatics XI, University of Dortmund, 44221, Dortmund, Germany

    Hans-Georg Beyer  & Hans-Paul Schwefel  & 

  4. Department of Signal Theory and Communications, Universidad Carlos III, Madrid, Spain

    José-Luis Fernández-Villacañas

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© 2002 Springer-Verlag Berlin Heidelberg

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Matsui, S., Watanabe, I., Tokoro, Ki. (2002). A Parameter-Free Genetic Algorithm for a Fixed Channel Assignment Problem with Limited Bandwidth. In: Guervós, J.J.M., Adamidis, P., Beyer, HG., Schwefel, HP., Fernández-Villacañas, JL. (eds) Parallel Problem Solving from Nature — PPSN VII. PPSN 2002. Lecture Notes in Computer Science, vol 2439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45712-7_76

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  • DOI: https://doi.org/10.1007/3-540-45712-7_76

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44139-7

  • Online ISBN: 978-3-540-45712-1

  • eBook Packages: Springer Book Archive

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