Title: The bee colony optimization algorithm and its convergence

Authors: Tatjana Jakšić Krüger; Tatjana Davidović; Dušan Teodorović; Milica Šelmić

Addresses: Mathematical Institute, Serbian Academy of Science and Arts, P.O. Box 367, Kneza Mihaila 36, 11001 Belgrade, Serbia ' Mathematical Institute, Serbian Academy of Science and Arts, P.O. Box 367, Kneza Mihaila 36, 11001 Belgrade, Serbia ' Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, Serbia ' Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, Serbia

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; swarm intelligence; honeybee foraging; BCO; bee colony optimisation; artifical bee colony; ABC; global optimisation; metaheuristics; stochastic processes; theoretical analysis; convergence properties.

DOI: 10.1504/IJBIC.2016.079573

International Journal of Bio-Inspired Computation, 2016 Vol.8 No.5, pp.340 - 354

Received: 02 Oct 2013
Accepted: 30 Apr 2014
Published online: 04 Oct 2016 *

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