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An Experimental Study of the Search Stagnation in Ants Algorithms

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Alaa Aljanaby
10.5120/ijca2016910861

Alaa Aljanaby. An Experimental Study of the Search Stagnation in Ants Algorithms. International Journal of Computer Applications 148(14):1-4, August 2016. BibTeX

@article{10.5120/ijca2016910861,
	author = {Alaa Aljanaby},
	title = {An Experimental Study of the Search Stagnation in Ants Algorithms},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2016},
	volume = {148},
	number = {14},
	month = {Aug},
	year = {2016},
	issn = {0975-8887},
	pages = {1-4},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume148/number14/25837-2016910861},
	doi = {10.5120/ijca2016910861},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This paper conducts experimental tests to study the stagnation behavior the Interacted Multiple Ant Colonies Optimization (IMACO) framework. The idea of different ant colonies use different types of problem dependent heuristics has been proposed as well. The performance of IMACO was demonstrated by comparing it with the Ant Colony System (ACS) the best performing ant algorithm. The computational results show the dominance of IMACO and that IMACO suffers less from stagnation than ACS.

References

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Keywords

Ant colony optimization, combinatorial optimization problems, search stagnation.