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 :
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