关键词: 菌群优化算法, 趋化步长, 聚类, 协同性

Abstract: In view of the defects of weak exploring ability and so on caused by the same swim step in the bacterial foraging algorithm, clustering idea is introduced to compute and adjust the swim step adaptively, which reflects the collaborative and intelligent behavior among bacterial population and can improve algorithm’s performance, such as exploration and exploitation, local search and refining ability. In the comparison experiment between this paper’s algorithm and other 4 typical algorithms on 10 complex Benchmark functions, this paper’s algorithm has better search ability and efficiency than the others up to 60%~90% among the test functions, which shows this paper’s algorithm is a competent algorithm for solving numerical optimization problems.

Key words: bacterial foraging optimization, chemotactic step size, clustering, coordination