An superior tracking artificial bee colony for global optimization problems
Xianghua Chu, Guozheng Hu, Ben Niu, Li Li, Zhengrong Chu · 2016
In order to improve the performance of original artificial bee colony (ABC) algorithm for global optimization problems in terms of solution accuracy and convergence speed, a superior tracking artificial bee colony (STABC) is presented in this paper. In STABC, the updating mechanism for bees is transformed from one-dimension-wise to all-dimension-wise. In addition, this strategy enables bees always to track the superior individuals in population. Experimental comparisons are conducted on twelve benchmark functions with various properties. Compared with the involved algorithms, experiment results demonstrate the remarkable improvement of the proposed algorithm for global optimization problems.