Improving the Bees Algorithm Using Gradual Search Space Reduction

The Bees Algorithm is a well-known metaheuristic optimisation method that has been applied in many disciplines with noticeable success. For example, it has been applied to machine scheduling, training artificial neural networks (ANNs) for pattern recognition, and the design of mechanical structures. There have been many attempts to improve the Bees Algorithm’s performance to tackle some of its weaknesses with more focus on the local search stage. This research attempts to improve the Bees Algorithm with more attention directed to stages other than the local search. The suggested method employs an adapted notion of the regional elimination method to achieve the abandonment and reduction of the search space within the Bees Algorithm. To assess the performance, the proposed method was tested on 24 benchmark functions, and it was applied to two engineering problems. The results obtained indicate a statistically significant improvement.