Bee Colony Optimization - part I: The algorithm overview
This paper is an extensive survey of the Bee Colony Optimization (BCO) algorithm, proposed for the first time in 2001. BCO and its numerous variants belong to a class of nature-inspired meta-heuristic methods, based on the foraging habits of honeybees. Our main goal is to promote it among the wide o...
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Veröffentlicht in: | Yugoslav Journal of Operations Research 2015, Vol.25 (1), p.33-56 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper is an extensive survey of the Bee Colony Optimization (BCO)
algorithm, proposed for the first time in 2001. BCO and its numerous variants
belong to a class of nature-inspired meta-heuristic methods, based on the
foraging habits of honeybees. Our main goal is to promote it among the wide
operations research community. BCO is a simple, but efficient meta-heuristic
technique that has been successfully applied to many optimization problems,
mostly in transport, location and scheduling fields. Firstly, we shall give a
brief overview of the other meta-heuristics inspired by bees? foraging
principles pointing out the differences between them. Then, we shall provide
the detailed description of the BCO algorithm and its modifications,
including the strategies for BCO parallelization, and giving the preliminary
results regarding its convergence. The application survey is elaborated in
Part II of our paper. |
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ISSN: | 0354-0243 1820-743X 2334-6043 |
DOI: | 10.2298/YJOR131011017D |