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Bee Colony Optimization (BCO)

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Part of the Studies in Computational Intelligence book series (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.

Keywords

  • Swarm Intelligence
  • Artificial Immune System
  • Forward Pass
  • Nurse Rostering
  • Artificial Node

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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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

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