Paper Info
Title
Analysis Of Population Size In Artificial Bee Colony Algorithm
Abstract
Artificial bee colony (ABC) algorithm has attracted growing interest for the continuous global optimization problems (CGOPs), where numerous algorithmic extensions have been developed. However, existing studies generally employ identical population size to perform the comparison among different ABC variants, regardless a fact that the generally suitable population size should be algorithm-dependent. Here we focus on the analysis of population size. This study is conducted in several wellknown ABC variants under a set of benchmark CGOPs. We demonstrate that i) with the independently optimal population size, standard ABC can perform competitively comparing with its advanced variants, and ii) the most remunerative population size is related to the algorithmic exploitation/exploration ability. We anticipate that this study will provide useful insights to guide the appropriate usage of ABC, as well as its further enhancements.
Year
DOI
Venue
2018
10.1109/SMC.2018.00615
2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
Field
DocType
ISSN
Artificial bee colony algorithm,Computer science,Population size,Artificial intelligence,Machine learning,Global optimization problem
Conference
1062-922X
Citations 
PageRank 
References 
0
0.34
0
Authors
7
Name
Order
Citations
PageRank
Xianneng Li1433.30
Meihua Yang211.37
Huiyan Yang311.37
Shizhe Wu400.34
Guangfei Yang522.06
Min Han676168.01
Shunshoku Kanae77811.91