Abstract: Aiming at the shortcomings of artificial bee colony(ABC) algorithm in solving complex problems,such as lower accuracy and slower convergence speed,a discrete artificial bee colony fusing the refraction learning and Lévy flight(DABC-RL) algorithm is proposed to design finite impulse response(FIR) low-pass digital filter,so as to further improve its filtering performance.In the DABC-RL algorithm,on the one hand,Lévy flight strategy is used to enhance its local search ability,and refraction learning is employed to enhance its global search ability.On the other hand,the candidate solution in the DABC-RL algorithm is discretized by designing an appropriate discrete coding scheme,which makes it suitable for designing FIR low pass digital filter.In order to test the performance of the FIR low-pass digital filter designed by the proposed DABC-RL algorithm,the FIR low-pass digital filters designed by ABC algorithm and the refrPSO algorithm based on the refraction learning is selected as two comparative algorithms.Experimental results and analysis show that compared with other algorithms,the FIR low-pass digital filter designed by DABC-RL algorithm has the best performance,and obtains the fastest convergence accuracy and convergence speed.

Key words: Multi-strategy discrete artificial bee colony algorithm, Refraction learning, Lévy flight, FIR low pass digital filter