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Bee Colony Optimization (BCO)

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Innovations in Swarm Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 248))

Abstract

Swarm Intelligence is the part of Artificial Intelligence based on study of actions of individuals in various decentralized systems. The Bee Colony Optimization (BCO) metaheuristic has been introduced fairly recently as a new direction in the field of Swarm Intelligence. Artificial bees represent agents, which collaboratively solve complex combinatorial optimization problem. The chapter presents a classification and analysis of the results achieved using Bee Colony Optimization (BCO) to model complex engineering and management processes. The primary goal of this chapter is to acquaint readers with the basic principles of Bee Colony Optimization, as well as to indicate potential BCO applications in engineering and management.

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Author information

Authors and Affiliations

  1. Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000, Belgrade, Serbia

    Dušan Teodorović

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  1. Dušan Teodorović
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Editors and Affiliations

  1. University of South Australia, Adelaide, Australia

    Chee Peng Lim  & Lakhmi C. Jain  & 

  2. Soft Computing Laboratory, Department of computer Science, Yonsei University, 120-749, Seoul, Korea

    Satchidananda Dehuri

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Teodorović, D. (2009). Bee Colony Optimization (BCO). In: Lim, C.P., Jain, L.C., Dehuri, S. (eds) Innovations in Swarm Intelligence. Studies in Computational Intelligence, vol 248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04225-6_3

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  • DOI: https://doi.org/10.1007/978-3-642-04225-6_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04224-9

  • Online ISBN: 978-3-642-04225-6

  • eBook Packages: EngineeringEngineering (R0)

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