%0 Journal Article
%A GUO Jia
%A MA Chao-bin
%A MIAO Meng-meng
%A ZHANG Shao-bo
%T Markov Chain Based Artificial Bee Colony Algorithm
%D 2020
%R 10.13190/j.jbupt.2019-063
%J Journal of Beijing University of Posts and Telecommunications
%P 54-60
%V 43
%N 1
%X To overcome the shortcomings of existing local search ability and to easily obtain the local optimal solution of artificial bee colony algorithm (ABC), a new modified artificial bee colony algorithm (MABC) is proposed using the development trend of known solution space predicted by Markov Chain. The running process of the algorithm is provided through a pseudo code. The performances of the ABC and MABC are analyzed from two aspects:convergence performance and algorithm complexity. Using 10 typical functions as test cases, Experiments are carried out in four aspects:result precision, convergence speed, segmentation parameters and running time. It is shown that the MABC algorithm is superior to the ABC algorithm in terms of accuracy and convergence speed.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2019-063