Research Article
Water-Tank Fish Algorithm: A New Metaheuristic for Optimization
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 182 - Issue 16 |
| Published: Sep 2018 |
| Authors: Madhup Sukoon, Haider Banka |
10.5120/ijca2018917835
|
Madhup Sukoon, Haider Banka . Water-Tank Fish Algorithm: A New Metaheuristic for Optimization. International Journal of Computer Applications. 182, 16 (Sep 2018), 1-5. DOI=10.5120/ijca2018917835
@article{ 10.5120/ijca2018917835,
author = { Madhup Sukoon,Haider Banka },
title = { Water-Tank Fish Algorithm: A New Metaheuristic for Optimization },
journal = { International Journal of Computer Applications },
year = { 2018 },
volume = { 182 },
number = { 16 },
pages = { 1-5 },
doi = { 10.5120/ijca2018917835 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2018
%A Madhup Sukoon
%A Haider Banka
%T Water-Tank Fish Algorithm: A New Metaheuristic for Optimization%T
%J International Journal of Computer Applications
%V 182
%N 16
%P 1-5
%R 10.5120/ijca2018917835
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper aims to introduce a new metaheuristic : TheWater-Tank Fish Algorithm, modeled after the workings of the swim bladder in fish, to non-deterministically compute the optima for numerical optimization problems. To balance the explorative-exploitative behavior of a search, the proposed method uses a search localization routine which, after a general exploration, restricts the search to certain areas of the graph and intensifies it as the algorithm advances. The proposed method is tested over 40 benchmark mathematical functions and the results were found to be very encouraging.
References
- Berat Dogan and Tamer O¨ lmez. A new metaheuristic for numerical function optimization: Vortex search algorithm. Information Sciences, 293:125–145, 2015.
- James Kennedy. Particle swarm optimization. In Encyclopedia of machine learning, pages 760–766. Springer, 2011.
- Esmat Rashedi, Hossein Nezamabadi-Pour, and Saeid Saryazdi. Gsa: a gravitational search algorithm. Information sciences, 179(13):2232–2248, 2009.
- S Salcedo-Sanz, J Del Ser, I Landa-Torres, S Gil-L´opez, and JA Portilla-Figueras. The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems. The Scientific World Journal, 2014, 2014.
- Sait Ali Uymaz, Gulay Tezel, and Esra Yel. Artificial algae algorithm (aaa) for nonlinear global optimization. Applied Soft Computing, 31:153–171, 2015.
- Xin-She Yang. A new metaheuristic bat-inspired algorithm. In Nature inspired cooperative strategies for optimization (NICSO 2010), pages 65–74. Springer, 2010.
Index Terms
Keywords