Authors: Jakšić Kruger, Tatjana 
Davidović, Tatjana 
Teodorović, Dušan
Šelmić, Milica
Title: The bee colony optimization algorithm and its convergence
Journal: International Journal of Bio-Inspired Computation
Volume: 8
Issue: 5
First page: 340
Last page: 354
Issue Date: 1-Jan-2016
Rank: M21a
ISSN: 1758-0366
DOI: 10.1504/IJBIC.2016.079573
Abstract: 
The bee colony optimization (BCO) algorithm is a nature-inspired meta-heuristic method for dealing with hard, real-life combinatorial and continuous optimisation problems. It is based on the foraging habits of honeybees and was proposed by Lučić and Teodorović in 2001. BCO is a simple, but effective meta-heuristic method that has already been successfully applied to various combinatorial optimisation problems in transport, location analysis, scheduling and some other fields. This paper provides theoretical verification of the BCO algorithm by proving some convergence properties. As a result, the gap between successful practice and missing theory is reduced.
Keywords: Bio-inspired algorithms | Convergence properties | Foraging of honeybees | Global optimum | Meta-heuristic methods | Optimisation problems | Stochastic processes | Swarm intelligence | The bco algorithm | Theoretical analysis
Publisher: Inderscience Publishers

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