|Authors:||Jakšić Kruger, Tatjana
|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|
Show full item record
checked on Feb 4, 2023
checked on Feb 5, 2023
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.