DocumentCode :
2167790
Title :
A hybrid search algorithm with Hopfield neural network and Genetic algorithm for solving traveling salesman problem
Author :
Vahdati, Gohar ; Ghouchani, Sima Yaghoubian ; Yaghoobi, Mahdi
Author_Institution :
Mashhad Branch, Comput. Dept., Islamic Azad Univ., Mashhad, Iran
Volume :
1
fYear :
2010
fDate :
26-28 Feb. 2010
Firstpage :
435
Lastpage :
439
Abstract :
In this paper, a hybrid search algorithm with Hopfield neural network (HNN) and Genetic algorithm (GA) is proposed. The HNN method is first used to generate valid solutions which are considered as solutions for initial population of genetic algorithm. Then, GA is used to perform exploitation around the best solution at each evaluation. The proposed algorithm has both the advantages of HNN and GA that can explore the search space and exploit the best solution. Experimental results demonstrate that the proposed algorithm does not get stuck at a local optimum.
Keywords :
Hopfield neural nets; genetic algorithms; search problems; travelling salesman problems; Hopfield neural network; genetic algorithm; hybrid search algorithm; traveling salesman problem; Ant colony optimization; Cities and towns; Computer networks; Cost function; Genetic algorithms; Genetic mutations; Hopfield neural networks; Performance evaluation; Space exploration; Traveling salesman problems; Genetic Algorithm; Heuristic Crossover; Hopfield Neural Network; Mutation; Traveling Salesman Problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5585-0
Electronic_ISBN :
978-1-4244-5586-7
Type :
conf
DOI :
10.1109/ICCAE.2010.5451917
Filename :
5451917
Link To Document :
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