Parameter Tuning for Bees Algorithm on Continuous Optimization Problems

Bees algorithm belongs to swarm intelligence category. It is a good algorithm for dealing with continuous optimization, though its main disadvantage is its six parameters being defined by users. Parameter setting is a notorious problem in swarm intelligence. This paper aims to tackle this issue by a parameter tuning strategy. Parameters are extensively studied with different combinations. Moreover, a popularly used numerical function set is taken in experiment with different dimensions. Experimental results are discussed and analyzed. The best ten parameter combinations are identified in terms of average number of function evaluations reaching global optima. They are useful for users to solve their real-world problems.

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