Artificial bee colony algorithm with comprehensive search mechanism for numerical optimization

2015 ◽  
Vol 26 (3) ◽  
pp. 603-617 ◽  
Author(s):  
Mudong Li ◽  
Hui Zhao ◽  
Xingwei Weng ◽  
Hanqiao Huang
2013 ◽  
Vol 284-287 ◽  
pp. 3168-3172
Author(s):  
Ren Bin Xiao ◽  
Ying Cong Wang

It is the research hotspot for evolutionary algorithms to solve the contradiction between exploration and exploitation. Cellular artificial bee colony (CABC) algorithm is proposed by combining cellular automata with artificial bee colony algorithm from the perspective of the neighborhood in this paper. Each bee in the population structure defined in CABC has a fixed position and can only interact with bees in its neighborhood. The overlap between neighborhoods of different bees may make a bee an employed bee in one neighborhood and an onlooker bee in another neighborhood and vice versa, which increases the diversity of the population. The neighborhood and evolutionary rule help to control the selection pressure effectively, and the improved search mechanism in artificial bee colony algorithm is proposed to enhance the local search ability. The experimental results tested on four benchmark functions show that CABC can further balance the relationship between exploration and exploitation when compared with three ABC-based algorithms.


2017 ◽  
Vol 417 ◽  
pp. 169-185 ◽  
Author(s):  
Laizhong Cui ◽  
Genghui Li ◽  
Xizhao Wang ◽  
Qiuzhen Lin ◽  
Jianyong Chen ◽  
...  

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