Abstract
Honey bees correctly allocate their work force to nectar sources using the “waggle dance”. In addition, they can determine the necessity for a nectar source. Thus, they possess a value threshold for a nectar source and they can collectively regulate it. Based on the mimicry of the threshold regulation used in honey bee foraging, we are developing a system that allows agents to determine whether their own solution is worth communicating to other agents. We propose a novel bio-inspired optimization algorithm, honey bee optimization (HBO). HBO is a multi-agent system based on the foraging activities of honey bees. To test the characteristics of HBO, we applied it to the travelling salesperson problem (TSP).
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© 2012 Springer-Verlag Berlin Heidelberg
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Furukawa, M., Suzuki, Y. (2012). Honey Bee Optimization Based on Mimicry of Threshold Regulation in Honey Bee Foraging. In: Watanabe, T., Watada, J., Takahashi, N., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia: Systems and Services. Smart Innovation, Systems and Technologies, vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29934-6_30
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DOI: https://doi.org/10.1007/978-3-642-29934-6_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29933-9
Online ISBN: 978-3-642-29934-6
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