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