A new metaheuristic for numerical function optimization: Vortex Search algorithm
By Berat Dogan, Tamer Ölmez. Information Sciences, 2015
365 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/11dca74c9d09953e151f1ae1d5cbce79bc11138b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Tansel Dökeroğlu
- Ali Asghar Heidari
- Huiling Chen
- Ahmet Cosar
- Tayfun Kucukyilmaz
- Ender Sevinç
- Iman Ahmadianfar
- Amir H. Gandomi
In Computational Theory and Mathematics
- Tansel Dökeroğlu
- Ali Asghar Heidari
- Huiling Chen
- Ahmet Cosar
- Tayfun Kucukyilmaz
- Ender Sevinç
- Iman Ahmadianfar
- Amir H. Gandomi
Citations in the corpus
- A survey on new generation metaheuristic algorithms (2019, background): “Doğan and Ölmez (2015) propose a new trajectory metaheuristic called Vortex Search (VS) algorithm to optimize numerical functions.”
- RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method (2021, methodology): “…PBAs include gravitational search algorithm (GSA) (Rashedi, et al., 2009), central force optimization (Formato, 2007), differential search (DS) (Liu, et al., 2015), vortex search algorithm (VSA) (Doğan & Ölmez, 2015), and gradient-based optimizer (GBO) (Ahmadianfar, Bozorg-Haddad, et al., 2020).”