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Water-Tank Fish Algorithm: A New Metaheuristic for Optimization

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Madhup Sukoon, Haider Banka
10.5120/ijca2018917835

Madhup Sukoon and Haider Banka. Water-Tank Fish Algorithm: A New Metaheuristic for Optimization. International Journal of Computer Applications 182(16):1-5, September 2018. BibTeX

@article{10.5120/ijca2018917835,
	author = {Madhup Sukoon and Haider Banka},
	title = {Water-Tank Fish Algorithm: A New Metaheuristic for Optimization},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2018},
	volume = {182},
	number = {16},
	month = {Sep},
	year = {2018},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume182/number16/29943-2018917835},
	doi = {10.5120/ijca2018917835},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, 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

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Keywords

Fish, Buoyancy, Metaheuristic, Nature Inspired, Optimization