Improved ant colony algorithm for continuous function optimization

Author(s):  
Xue Xue ◽  
Wei Sun ◽  
Chengshi Peng
2014 ◽  
Vol 1049-1050 ◽  
pp. 530-534
Author(s):  
Xiao Ping Zong ◽  
Hai Bin Zhang ◽  
Lei Hao ◽  
Pei Guang Wang

Because of the drift which exists in sequence image of prostate DWI (Diffusion Weighted Imaging), the global ant colony algorithm is introduced into the paper for registration optimization. The paper introduces an ant colony algorithm for continuous function optimization, based on max-min ant system (MMAS). This paper controls the transition probabilities and enhances the abilities of ants seeking globally optimal solutions by adding an adjustable factor in the basic ant colony algorithm and updating the local pheromone and global pheromone. Experimental results verify the effectiveness of the algorithm.


2013 ◽  
Vol 347-350 ◽  
pp. 3450-3455 ◽  
Author(s):  
Ting Wei Liu ◽  
Hong Bo Wang ◽  
Yang Dang ◽  
Shu Ren Yang

In this paper, an Improved Ant Colony Algorithm is applied to the identification of the ship motion modelNomotos 1st-order nonlinear model. A robust method based on Ant Colony Algorithm is proposed for the optimization of the continuous function. The transfer criterion of the ants between each layer and global pheromone updating process are described. Some experiments results show that this method has good identification accuracy. The algorithm is feasible and effective, is of enormous significance to the system identification of ship motion.


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