DocumentCode
1752836
Title
A Convergence Proof for Ant Colony Algorithm
Author
Zhao, Baojiang ; Li, Shiyong
Author_Institution
Dept. of Control Sci. & Eng., Harbin Inst. of Technol.
Volume
1
fYear
0
fDate
0-0 0
Firstpage
3072
Lastpage
3075
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location
Dalian
Print_ISBN
1-4244-0332-4
Type
conf
DOI
10.1109/WCICA.2006.1712931
Filename
1712931
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