Title :
A Convergence Proof for Ant Colony Algorithm
Author :
Nong, Jifu ; Jin, Long
Author_Institution :
Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning, China
Abstract :
In this paper, a general framework for solving combinatorial optimization problems heuristically by the ant system approach is developed. Based on the two different conditions, some convergence properties for ant colony system (ACS) are presented. The global searching and convergence ability are improved by adaptively changing the lower pheromone bound. It is shown that ACS is guaranteed to find an optimal solution with probability.
Keywords :
combinatorial mathematics; optimisation; probability; ant colony algorithm; combinatorial optimization problems; convergence proof; optimal solution; pheromone bound; probability; Ant colony optimization; Computer science; Convergence; Educational institutions; Mathematics; Meteorology; Minimization methods; Shortest path problem; Simulated annealing; Stochastic processes; Ant colony optimization; Convergence; Metaheuristic;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.305
