Empirical study of the Bee Colony Optimization (BCO) algorithm

The Bee Colony Optimization (BCO) meta-heuristic deals with combinatorial optimization problems. It is biologically inspired method that explores collective intelligence applied by the honey bees during nectar collecting process. In this paper we perform empirical study of the BCO algorithm. We apply BCO to optimize numerous numerical test functions. The obtained results are compared with the results in the literature. The numerical experiments performed on well-known benchmark functions show that the BCO is competitive with other methods and it can generate high-quality solutions within negligible CPU times.

► We apply Bee Colony Optimization (BCO) to optimize numerous numerical test functions.
► The numerical experiments performed on well-known benchmark functions.
► The obtained results are compared with the up-to-date metaheuristic algorithms.
► BCO can generate high-quality solutions within negligible CPU times.
► The BCO is competitive with other methods.