Abstract:

We propose an improved artificial bee colony (ABC) algorithm to overcome the drawbacks of slow convergence rate and low optimization precision of the conventional ABC algorithm. The selfadaptive chemotaxis and guiding factors are introduced into the search schemes of employed bees and onlooker bees, respectively. Under the guidance of the guiding factors, the local search capability is significantly improved due to the employed bees’ dynamic search for the high quality nectar sources and the onlooker bees’ cooperative search for the better nectar sources. Simulation results based on the eight standard functions show that the improved ABC algorithm is superior to the conventional one in both computational accuracy and convergence rate.

Key words: artificial bee colony algorithm;local search;search scheme;self-adaptive chemotaxis;guiding factor