关键词: 人工蜂群算法, 当前最优解, 混沌算子, 细菌趋药性

Abstract: The standard artificial bee colony algorithm is limited in solving minimum function optimization problems because of the poor local search ability, low computational precision of convengence and easily to fall to local optimum. Attempting to solve the problems emphasized above, this paper proposes an advanced artificial bee colony algorithm. This algorithm introduces chaos operator into the local search strategy of employed bees and onlooker bees, which is based on the current optimal solution. Also, this algorithm introduces bacterial chemotaxis behavior into onlooker bees to improve its local search ability. The simulation results of six test functions show that the algorithm can effectively avoid getting into local optimum, and the convergence accuracy is significantly improved.

Key words: artificial bee colony, current optimal, chaos operator, bacterial chemotaxis behavior