Article ID Journal Published Year Pages File Type
382690 Expert Systems with Applications 2013 12 Pages PDF
Abstract

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.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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