A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications

被引：109
作者：
Abualigah, Laith [1 ]
Diabat, Ali [2 ,3 ]
Geem, Zong Woo [4 ]
机构：
[1] Amman Arab Univ, Fac Comp Sci & Informat, Amman 11953, Jordan
[2] New York Univ Abu Dhabi, Div Engn, Abu Dhabi 129188, U Arab Emirates
[3] NYU, Tandon Sch Engn, Dept Civil & Urban Engn, Brooklyn, NY 11201 USA
[4] Gachon Univ, Dept Energy IT, Seongnam 13120, South Korea
来源：
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 11期
基金：
新加坡国家研究基金会;
关键词：
harmony search algorithm; meta-heuristic optimization algorithms; optimization problems; clustering applications; PARTICLE SWARM OPTIMIZATION; TEXT FEATURE-SELECTION; KRILL HERD ALGORITHM; HYBRID; STRATEGY; PROTOCOL; DESIGN;
D O I：
10.3390/app10113827
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions.
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收藏
页数：26
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