Title :
Ant Colony Algorithm Based on Chaos Annealing
Author :
Hui, Xiong ; Chunbo, Xiu
Author_Institution :
Dept. of Autom. Control, Tianjin Polytech. Univ., Tianjin, China
Abstract :
A new ant colony optimization algorithm is proposed to resolve combinatorial optimization problem. The performance of the optimization algorithm can be improved by the chaos annealing. In the incipient optimization process, ants search the new path not only according to the concentration of the pheromone, but also the chaos guidance, which make the algorithm have the stronger ergodicity searching ability. In the terminal optimization process, the chaos decayed to zero gradually. In the end, the algorithm transforms into the conventional ant colony algorithm and completes the optimal process by the principle of pheromone positive feedback, which insures the algorithm to have a quick convergence rate. The simulation results prove the validity of the algorithm.
Keywords :
combinatorial mathematics; simulated annealing; ant colony algorithm; chaos annealing; combinatorial optimization; pheromone positive feedback; Annealing; Ant colony optimization; Application software; Chaos; Chaotic communication; Cities and towns; Computer applications; Convergence; Feedback; Traveling salesman problems; Annealing; Ant colony; Chaos; Combinatorial optimization;
Conference_Titel :
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location :
Chongqing
Print_ISBN :
978-0-7695-3930-0
Electronic_ISBN :
978-1-4244-5423-5
DOI :
10.1109/IFCSTA.2009.50