Artificial Bee Colony is a population-based metaheuristic optimization algorithm that mimics the foraging behavior of honey bees, distinguishing itself by employing employed, onlooker, and scout bee phases to iteratively explore and exploit search spaces for optimal solutions.
4.3K
Publications
265.8K
Citations
9.7K
Authors
2.4K
Institutions
Publications per year
2017–2026
2.1K
Parents
Publications
4.3K
On the performance of artificial bee colony (ABC) algorithm
Derviş Karaboğa · Applied Soft Computing · 2007 · 3.7K citations
1–5 of 4.3K
Authors
9.7K
- DK
41
h-index
- QP
28
h-index
- BA
25
h-index
- CÖ
23
h-index
- DT
19
h-index
1–5 of 9.7K
Institutions
2.4K
Erciyes University
Kayseri, Türkiye
53 h-index
255 publications
55.5K citations
Huazhong University of Science and Technology
Wuhan, China
41 h-index
211 publications
12.3K citations
Liaocheng University
Liaocheng, China
33 h-index
88 publications
9K citations
Chinese Academy of Sciences
Beijing, China
29 h-index
137 publications
7.5K citations
Beihang University
Beijing, China
27 h-index
97 publications
6.2K citations
University of Tehran
Tehran, Iran
27 h-index
60 publications
2.8K citations
Wuhan University of Technology
Wuhan, China
26 h-index
123 publications
6.8K citations
Hong Kong Polytechnic University
Hong Kong, Hong Kong
25 h-index
56 publications
3.3K citations
1–8 of 2.4K
Venues
- Applied Soft Computing
160 publications · 19.7K citations
70
h-index
- IEEE Access
137 publications · 8K citations
48
h-index
- Expert Systems with Applications
71 publications · 9.3K citations
43
h-index
- Information Sciences
56 publications · 7.1K citations
43
h-index
- Neural Computing and Applications
53 publications · 3.7K citations
33
h-index
1–5