文档介绍：References
D. Karaboga, An idea based on honey bee swarm for numerical optimization. Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, 2005
B. Basturk, D. Karaboga, An artificial bee colony (abc) algorithm for numeric function optimization, in: IEEE Swarm Intelligence Symposium 2006,Indianapolis, Indiana, USA, May 2006.
D. Karaboga, B. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm,Journal of Global Optimization 39 (3) (2007) 459–471.
D. Karaboga, B. Basturk, On the performance of artificial bee colony (abc) algorithm, Applied Soft Computing 8 (1) (2008) 687–697.
D. Karaboga,,A comparative study of artificial bee colony algorithm,Applied Mathematics and Computation 214 (2009) 108-132
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Two fundamental concepts:self-organization and division of labour
Self organization relies on four basic properties : positive feedback,negative feedback,fluctuations and multiple interactions
Division of labour is believed to be more efficient than the sequential task performance. It also enables the swarm to respond to changed conditions in the search space.
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OF HONEY BEE SWARM
The emergence of collective intelligence of honey bee swarms consists of three essential components:
Food sources
Employed foragers
Unemployed foragers
the model defines two leading modes of the behaviour:
The recruiment to a nectar source
The abandonment of a source
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OF HONEY BEE SWARM
There are two possible options for such a bee:
i) It can be a scout and starts searching around the nest spontaneously for a food due to some internal motivation or possible external clue (S on Figure 1).
ii) It can be a recruit after watching the waggle dances and starts searching for a food source (R on Figure 1).
After unloading the food, the bee has the following three options:
i) It becomes an uncom