关键词: 人工蜂群算法, 可调压排序选择策略, 动态调整策略集, 函数优化

Abstract: To overcome the defects of convergence speed and the local optimum of artificial bee colony algorithm, this  paper  proposes an improved artificial bee colony algorithm based on multi-strategy fusion. In order to maintain the population diversity and avoid the local optimum, this paper imports the strategy of adjustable voltage ranking selection. To accelerate the convergence rate of artificial bee colony algorithm, a dynamic adjustment strategy set is composed of linear adjustment global guidance strategy, adaptive dynamic adjustment factor strategy and updating strategy of standard artificial swarm algorithm in following bee stage. The policy is dynamically adjusted by comparing the current update value of the food source with the last iterative update value. Through the simulation experiment on a suite of standard functions, the results show that the algorithm has a faster convergence rate and higher solution accuracy, and less number of iterations.

Key words: artificial bee colony algorithm, adjustable voltage selection strategy, dynamic adjustment strategy set, function optimization