关键词: 人工蜂群算法, 目标函数值信息, 自适应, 改进搜索策略, 高斯分布

Abstract: The basic artificial bee colony algorithm and its search strategy focus on exploration. In order to enhance the exploitation of the algorithm, this paper proposes a hybrid artificial bee colony algorithm with adaptive search strategy and better exploitation. Firstly, the objective function value information and optimal solution guiding information are introduced into the search strategy, so that this paper obtains a new search strategy with strong exploitation and self-adaptive mechanism; At the same time, in order to avoid premature convergence, this paper uses three random food sources and Gaussian distribution to form a new search strategy with good exploration. And then, this paper balances exploration and exploitation by hybridizing the two search strategies in employed bee phase, and enhances exploitation by using the search strategy with strong exploitation in onlooker bee phase. Compared with basic and some representative improved artificial bee colony algorithms in 20 standard test functions, the experimental results show that the proposed algorithm has better search ability and faster convergence speed.

Key words: artificial bee colony algorithm, information of objective function value, self-adaption, improved search , strategy, Gaussian distribution