DocumentCode
3262225
Title
Convergence of ant colony optimization on first-order deceptive systems
Author
Chen, Yixin ; Sun, Haiying
Author_Institution
Dept. of Comput. Sci. & Eng., Washington Univ. in St. Louis, St. Louis, MO
fYear
2008
fDate
26-28 Aug. 2008
Firstpage
158
Lastpage
163
Abstract
Deceptive problems have been considered difficult for ant colony optimization (ACO) and it was believed that ACO will fail to converge to global optima of deceptive problems. This paper presents a convergence analysis of ACO on deceptive systems. This paper proves, for the first time, that ACO can achieve reachability convergence but not asymptotic convergence for a class of first order deceptive systems (FODS) without assuming a minimum pheromone at each iteration. Experimental results confirm the analysis.
Keywords
convergence of numerical methods; optimisation; ant colony optimization; asymptotic convergence; convergence analysis; first-order deceptive systems; global optima; Ant colony optimization; Computer science; Convergence; Genetic algorithms; Stochastic processes; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2008. GrC 2008. IEEE International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-2512-9
Electronic_ISBN
978-1-4244-2513-6
Type
conf
DOI
10.1109/GRC.2008.4664719
Filename
4664719
Link To Document