Abstract
We need an efficient channel assignment algorithm for increasing channel re-usability, reducing call-blocking rate and reducing interference in any cellular systems with limited bandwidth and a large number of subscribers. We propose an efficient hybrid genetic algorithm for a fixed channel assignment problem with limited bandwidth constraint. 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 produces far better solutions to several practical problems than existing GAs.
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References
Bierwirth, C., Mattfeld, D.C., and Kopfer, H.: On permutation representations for scheduling problems, Proc. 4th International Conference on Parallel Problem Solving from Nature-PPSN IV, pp.310–318, 1996.
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.
Cuppini, M.: A genetic algorithm for channel assignment problems, Eur. Trans. Telecommun., vol.5, no.2, pp.285–294, 1994.
Horng, J.T., Jin, M.H., and Kao, C.Y.: Solving fixed channel assignment problems by an evolutionary approach, Proc. of Genetic and Evolutionary Computation Conference 2001 (GECCO-2001), pp.351–358, 2001.
Hurley, S. and Smith, D.H.: Fixed spectrum frequency assignment using natural algorithms, Proc. of Genetic Algorithms in Engineering Systems: Innovations and Applications, pp.373–378, 1995.
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.
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. IEEE Int. Conf. Commun. 2001, vol.7, pp.2100–2104, 2001.
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.
Lai, K.W. and Coghill, G.G.: Channel assignment through evolutionary optimization, IEEE Trans. Veh. Technol., vol.45, no.1, pp.91–96, 1996.
Matsui, S. and Tokoro, K.: A new genetic algorithm for minimum span frequency assignment using permutation and clique, Proc. of Genetic and Evolutionary Computation Conference 2000 (GECCO-2000), pp.682–689, 2000.
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 Genetic and Evolutionary Computation Conference 2001 (GECCO-2001), pp.1359–1366, 2001.
Mitchell, M.:An Introduction to Genetic Algorithms, MIT Press, 1996.
Moscate, P: On evolution, search, optimization, genetic algorithms and martial arts: towards memetic algorithms, Caltech Concurrent Computation Program, C3P Report 826, 1989.
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.
Park, E. J., Kim, Y. H., and Moon, B. R., Genetic search for fixed channel assignment problem with limited bandwidth, Proc. of Genetic and Evolutionary Computation Conference 2002 (GECCO-2002), pp.1172–1179, 2002.
Rothlauf, F., Goldberg, D.E., and Heinzl, A.: Bad coding and the utility of well-designed genetic algorithms, Proc. of Genetic and Evolutionary Computation Conference 2000 (GECCO-2000), pp. 355–362, 2000.
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.
Smith, J.E.: Self Adaptation in Evolutionary Algorithms, Ph.D thesis, Univ. of the West England, Bristol, 1998.
Valenzuela, C., Hurley, S., and Smith, D.: A permutation based algorithm for minimum span frequency assignment, Proc. 5th International Conference on Parallel Problem Solving from Nature—PPSN V, Amsterdam, pp. 907–916, 1998.
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Matsui, S., Watanabe, I., Tokoro, Ki. (2003). An Efficient Hybrid Genetic Algorithm for a Fixed Channel Assignment Problem with Limited Bandwidth. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_118
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DOI: https://doi.org/10.1007/3-540-45110-2_118
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