Artificial Bee Colony Algorithm with Global and Unbiased Search Strategy
DU Zhen-xin1,2, LIU Guang-zhong1, HAN De-zhi1, YU Xue-shan1, JIA Jian-xin1
1. College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China;
2. School of Computer Information Engineering, Hanshan Normal University, Chaozhou, Guangdong 521041, China
Abstract：To settle the contradictory between convergence speed and precocity in artificial bee colony with elite-guided equations (ABC_elite),an enhanced ABC_elite (EABC_elite) is proposed.In the employed bee phase of EABC_elite,the global best (gbest) individual is introduced to the search equation to accelerate convergence,while the ordinary individual is also introduced to the search equation to balance the gbest's great lead ability,thus the information of gbest and ordinary individuals can all be used and the balance between exploration and exploitation can still be maintained.In the onlooker bee phase of EABC_elite,the ordinary individual is also introduced into the search equation to avoid the precocity.EABC_elite can keep good balance between accelerating convergence and averting precocity.It has no bias to any search directions and the global search ability of ABC_elite is enhanced.The experimental results demonstrate that EABC_elite performs significantly better than ABC_elite and other recently-developed state-of-the-art variants of artificial bee colony algorithm.
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2018, Vol. 46 
