It has always been a problem faced by Artificial Bee Colony (ABC) algorithm that how to adjust exploration and exploitation dynamically in the evolution process. In order to overcome this problem, this paper presents a highly efficient variant of ABC algorithm which is two-strategy adaptive. Among the two proposed search strategies, one has strong exploration ability and the other has strong exploitation ability; Based on the adaptability of the two search strategies to the problem solving and the search process, the selection probability of each search strategy is dynamically adjusted according to success rate, and then the cooperative optimization of the two search strategies is realized to improve the performance of the algorithm. It can be seen that the improved algorithm is enhanced significantly on accuracy of solution and success rate from comparing experiment results with the other state-of-the-art ABC algorithms.

人工蜂群（ABC）算法一直面临着一个问题，即如何在进化过程中动态地调整勘探与开发。为了克服这个问题，本文提出了一种高效的ABC算法变体，它是两种策略的自适应方法。在提出的两种搜索策略中，一种具有较强的探索能力，另一种具有较强的利用能力。基于两种搜索策略对问题求解和搜索过程的适应性，根据成功率动态调整每种搜索策略的选择概率，然后实现两种搜索策略的协同优化，以提高搜索性能。算法。