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
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;
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
DOI :
10.1109/CEC.2013.6557793