Application of the parameter-free genetic algorithm to the fixed channel assignment problem

@article{Matsui2005ApplicationOT,
  title={Application of the parameter-free genetic algorithm to the fixed channel assignment problem},
  author={Shouichi Matsui and Isamu Watanabe and Ken-ichi Tokoro},
  journal={Systems and Computers in Japan},
  year={2005},
  volume={36},
  pages={71-81}
}
This paper is concerned with the application of the parameter-free genetic algorithm (PfGA) proposed by Sawai and colleagues and the parallel distributed PfGA, to the fixed channel assignment problem. The results of the investigation are presented. The PfGA does not include parameters such as the population size, the crossover rate, and the mutation rate, which have been indispensable in the conventional genetic algorithm (GA). This eliminates parameter tuning for each problem, which is a very… CONTINUE READING
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References

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Showing 1-10 of 30 references

Efficient utilization of frequency spectrum for mobile communication systems—Algorithms for channel assignments

  • M. Sengoku
  • Proc IEICE 1984;69:350–356
  • 1984
Highly Influential
5 Excerpts

A fast genetic algorithm using allocation order for fixed channel assignment in mobile communications

  • S Matsui, K. Tokoro
  • Trans IEICE
  • 2000
Highly Influential
5 Excerpts

FAP web—A website about frequency assignment problems

  • A Eisenblätter, A. Koster
  • http://fap.zib.de/, last modified Oct
  • 2001

Effects of migration methods in parallel distributed parameter - free genetic algorithm

  • S Adachi, H Sawai
  • Trans IEICE
  • 2000

Effects of migration methods in parallel distributed parameter-free genetic algorithm. Trans IEICE 2000;J83-D-I:834–843

  • S Adachi, H. Sawai
  • 2000

Fixed channel allocation method in mobile radio communications using the genetic algorithm

  • H Murakami, K Ogawa, T. Ohgane
  • Trans IEICE 2000;J83B:769–779
  • 2000
2 Excerpts

Adapting genetic operators and GA parameters based on elite degree of an individual in a genetic algorithm

  • K Hatta, S Wakabayashi, T. Koide
  • Trans IEICE 1999;J82-D-I:1135–1143
  • 1999

Parameter-free genetic algorithm (PfGA) using adaptive search with variable-size local population and its extension to parallel distributed processing

  • S Kizu, H Sawai, S. Adachi
  • Trans IEICE 1999;J82-DII:512–521
  • 1999

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