Discussions of worker ants' rule-based CHC dealing with changing environments

@article{Kamiya2010DiscussionsOW,
  title={Discussions of worker ants' rule-based CHC dealing with changing environments},
  author={A. Kamiya and K. Abiko and S. Kobayashi},
  journal={Appl. Soft Comput.},
  year={2010},
  volume={10},
  pages={245-250}
}
  • A. Kamiya, K. Abiko, S. Kobayashi
  • Published 2010
  • Computer Science
  • Appl. Soft Comput.
  • Contrary to popular belief, biologists discovered that worker ants are really not all hardworking. It has been found that in three separate 30-strong colonies of black Japanese ants (Myrmecina nipponica), about 20% of worker ants are diligent, 60% are ordinary, and 20% are lazy. That is called 20:60:20 rule. Though they are lazy, biologists suggested that lazy worker ants could be contributing something to the colony that is yet to be determined. In our last research, we used CHC (cross… CONTINUE READING
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    SHOWING 1-10 OF 23 REFERENCES
    Worker ants' rule-based genetic algorithms dealing with changing environments
    • A. Kamiya, F. Makino, S. Kobayashi
    • Computer Science
    • Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05.
    • 2005
    • 5
    • PDF
    Ant system: optimization by a colony of cooperating agents
    • 10,410
    • PDF
    The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination
    • 1,105
    • Highly Influential
    Multinational GAs: Multimodal Optimization Techniques in Dynamic Environments
    • 174
    • PDF
    Genetic Algorithms for Tracking Changing Environments
    • 424
    • PDF
    Evolutionary optimization in uncertain environments-a survey
    • Y. Jin, J. Branke
    • Mathematics, Computer Science
    • IEEE Transactions on Evolutionary Computation
    • 2005
    • 1,400
    • PDF
    Multiobjective optimization immune algorithm in dynamic environments and its application to greenhouse control
    • Z. Zhang
    • Computer Science
    • Appl. Soft Comput.
    • 2008
    • 103
    A hybrid GA approach for solving the Dynamic Vehicle Routing Problem with Time Windows
    • 26
    Genetic Algorithms for Changing Environments
    • 616
    • Highly Influential
    • PDF
    Supporting Polyploidy in Genetic Algorithms Using Dominance Vectors
    • 70