Title :
A Convergence Proof for Ant Colony Algorithm
Author :
Zhao, Baojiang ; Li, Shiyong
Author_Institution :
Dept. of Control Sci. & Eng., Harbin Inst. of Technol.
Abstract :
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 1
Keywords :
artificial life; convergence; heuristic programming; optimisation; probability; search problems; ant colony algorithm; ant colony system; combinatorial optimization; convergence proof; metaheuristic; Algorithm design and analysis; Ant colony optimization; Convergence; Cost function; Educational institutions; Mathematics; Shortest path problem; Simulated annealing; Stochastic processes; Ant colony optimization; ant colony System; convergence; metaheuristic;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1712931
