DocumentCode :
2927439
Title :
A Study of Stimulative Queen Ant Strategy in Ant Colony Optimization Method
Author :
Iimura, Ichiro ; Ito, Toshiya ; Nakayama, Shigeru
Author_Institution :
Fac. of Adm., Prefectural Univ. of Kumamoto
fYear :
2006
fDate :
Dec. 2006
Firstpage :
180
Lastpage :
184
Abstract :
Ant colony optimization (ACO) methods, which imitate a mechanism of pheromone secretion when ants carry food to their nest, are one of efficient heuristic search methods for combinational optimization problems such as traveling salesman problems (TSPs) and so on. In this paper, we analyze the queen ant strategy ASqueen that is one of ACO methods more in detail by applying it to six kinds of city configurations included in the TSPLIB. Furthermore, in order to improve searching ability of the ASqueen, we propose a new method named "stimulative queen ant strategy ASS queen". As experimental results, we have clarified that the ASS queen shows better performance than the conventional ASqueen in the viewpoint of both "discovery rate of optimal solution" and "average number of iterations"
Keywords :
artificial intelligence; optimisation; search problems; ant colony optimization; combinational optimization; heuristic search method; pheromone secretion; stimulative queen ant strategy; Ant colony optimization; Cities and towns; Concurrent computing; Distributed computing; Fluids and secretions; Indium tin oxide; Large-scale systems; Search methods; Traveling salesman problems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Computing, Applications and Technologies, 2006. PDCAT '06. Seventh International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7695-2736-1
Type :
conf
DOI :
10.1109/PDCAT.2006.21
Filename :
4032174
Link To Document :
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