DocumentCode
1752886
Title
Convergence Analysis of a Class of Adaptive 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
3524
Lastpage
3527
Abstract
This paper presents a class of adaptive ant colony optimization algorithm and proves its convergence properties. The global searching and convergence ability are improved by adaptively changing the pheromone trails evaporation factors and decreasing lower pheromone bound. Markov process analysis is used to prove convergence properties of the algorithms. It is shown that its current solutions of the system converge, with probability one, to an optimal solution of the system
Keywords
Markov processes; artificial life; convergence of numerical methods; optimisation; Markov process analysis; adaptive ant colony optimization; convergence analysis; global searching; pheromone trails evaporation factors; Algorithm design and analysis; Ant colony optimization; Convergence; Educational institutions; Markov processes; Mathematics; Simulated annealing; Stochastic processes; Ant colony optimization; convergence; markov process;
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.2006.1713024
Filename
1713024
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