Adaptive generalized crowding for genetic algorithms

  title={Adaptive generalized crowding for genetic algorithms},
  author={Ole J. Mengshoel and Severino F. Gal{\'a}n and Antonio de Dios},
  journal={Inf. Sci.},
The genetic algorithm technique known as crowding preserves population diversity by pairing each offspring with a similar individual in the current population (pairing phase) and deciding which of the two will survive (replacement phase). The replacement phase of crowding is usually carried out through deterministic or probabilistic crowding, which have the limitations that they apply the same selective pressure regardless of the problem being solved and the stage of genetic algorithm search… CONTINUE READING
7 Citations
42 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 42 references

Efficient Bayesian Network Inference: Genetic Algorithms, Stochastic Local Search, and Abstraction

  • O. J. Mengshoel
  • PhD thesis, Department of Computer Science,
  • 1999
Highly Influential
4 Excerpts

Niching Methods for Genetic Algorithms

  • S. W. Mahfoud
  • PhD thesis, Department of General Engineering,
  • 1995
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…