DocumentCode :
2563384
Title :
An Adaptive Parameter Control Strategy for Ant Colony Optimization
Author :
Ling, Wei-xin ; Luo, Huan-ping
fYear :
2007
fDate :
15-19 Dec. 2007
Firstpage :
142
Lastpage :
146
Abstract :
proved to be one of the best performing algorithms for NP-hard combinational optimization problems like TSP. Many researchers have been attracted in research for ACO but fewer tuning methodologies have been done on its parameters which influence the algorithm directly. The setting of ACO´s parameters is studied in this paper. The Artificial Fish Swarm Algorithm (AFSA) is introduced to solve the parameter tuning problem, and an adaptive parameter setting strategy is proposed. It´s proved to be effective by the experiment based on TSPLIB test. Keywords: Artificial Fish Swarm Algorithm, Ant Colony Optimization, parameters, TSP
Keywords :
Adaptive control; Ant colony optimization; Computational intelligence; Educational institutions; Equations; Marine animals; Programmable control; Robust control; Security; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2007 International Conference on
Conference_Location :
Harbin
Print_ISBN :
0-7695-3072-9
Electronic_ISBN :
978-0-7695-3072-7
Type :
conf
DOI :
10.1109/CIS.2007.156
Filename :
4415319
Link To Document :
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