DocumentCode
618042
Title
A less exploitative variation of the Enhanced Ant Colony System applied to SOP
Author
Ezzat, Ahmed ; Abdelbar, Ashraf
Author_Institution
Dept. of Comput. Sci. & Eng., American Univ. in Cairo, Cairo, Egypt
fYear
2013
fDate
20-23 June 2013
Firstpage
1917
Lastpage
1924
Abstract
The Ant Colony System (ACS) model tends to favor exploitation over exploration, relative to other Ant Colony Optimization (ACO) models. Gambardella et al. (2012) have introduced an Enhanced ACS (EACS) that is even more exploitative than ACS, and have found that EACS improves performance on several problems, including the Sequential Ordering Problem (SOP). In this paper, we propose a variation on EACS that is less exploitative than EACS, but still more exploitative than ACS. Evaluating our model on SOP, and using the same library of instances as Gambardella et al., we find that our model improves performance to a statistically significant extent.
Keywords
ant colony optimisation; combinatorial mathematics; EACS; ant colony system; discrete combinatorial optimization; enhanced ACS; less exploitative variation; sequential ordering problem; Ant colony optimization; Data structures; Equations; Mathematical model; Search problems; Standards; Stochastic processes; Ant Colony System (ACS); Combinatorial Optimization; Holland´s Exploitation-Exploration Tradeoff; Sequential Ordering Problem (SOP); State Space Search; Statistical Significance; Swarm Intelligence; Wilcoxon Signed-Ranks Test;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location
Cancun
Print_ISBN
978-1-4799-0453-2
Electronic_ISBN
978-1-4799-0452-5
Type
conf
DOI
10.1109/CEC.2013.6557793
Filename
6557793
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