关键词: 人工蜂群算法, 函数优化, 邻域搜索, 自适应, 非线性函数

Abstract: A modified Artificial Bee Colony (ABC) algorithm was proposed for numerical function optimization in this paper, in order to solve the problems of slow convergence and low computational precision of conventional ABC algorithm. The modified ABC algorithm can adjust the step size of the selected neighbor food source position adaptively according to the objective function. On the other hand, the searching method based on a nonlinear adjustment of search range depending on the iteration was introduced for scout bees. The modified ABC algorithm can improve the exploitation, and avoids the premature convergence effectively. The experimental results on six benchmark functions show that, the modified ABC algorithm significantly improves the optimization ability. The modified ABC algorithm can achieve the global minimum values for numerous multimodal functions with high dimension. Compared to the other approaches, the proposed method not only obtains higher quality solutions, but also has a faster convergence speed.

Key words: Artificial Bee Colony (ABC), numerical function optimization, neighborhood position, adaptive, nonlinear function