DocumentCode :
2558427
Title :
An improved genetic Hopfield neural networks based on probability model for solving travelling salesman problem
Author :
Yang, Huafen ; Dong, Dechun ; Yang, You ; Zhang, Lihui
Author_Institution :
Dept. of Comput. Sci. & Eng., Qujing Normal Coll., Qujing, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
168
Lastpage :
171
Abstract :
The existing problems of Hopfield neural networks solving travelling salesman problem are analysed and improved energy function is proposed in this paper. Probablity model is introduced into improved HNNs. Probablity model records the gene information of the best individuals,which can make genetic algorithm search simultaneously in depth and width. An improved genetic hopfield neural networks based on probability model is proposed, which not only reduces the rate of invalid tours, but also avoids random search. Simulation experiments show that it can accelerate the convergent speed and enhance the searching ability.
Keywords :
Hopfield neural nets; convergence; genetic algorithms; probability; travelling salesman problems; HNN; convergent speed; energy function; gene information; improved genetic Hopfield nerual networks; invalid tours; probability model; travelling salesman problem; Cities and towns; Educational institutions; Genetic algorithms; Genetics; Hopfield neural networks; Neurons; Traveling salesman problems; Hopfield neural networks; external population; genetic algorithm; probability model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234626
Filename :
6234626
Link To Document :
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