A hybrid parallel genetic algorithm and its application to TSP

Dai Xiaoming; Zou Runmin; Feng Rui; Zhang Hongyuan; Shao Huihe

Volume 24 Issue 10

Oct. 2002

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2002 > 24(10): 1424-1427

Dai Xiaoming, Zou Runmin, Feng Rui, Zhang Hongyuan, Shao Huihe. A hybrid parallel genetic algorithm and its application to TSP[J]. Journal of Electronics & Information Technology, 2002, 24(10): 1424-1427.

Citation:

Dai Xiaoming, Zou Runmin, Feng Rui, Zhang Hongyuan, Shao Huihe. A hybrid parallel genetic algorithm and its application to TSP[J]. Journal of Electronics & Information Technology, 2002, 24(10): 1424-1427.

Citation:

PDF( 747 KB)

A hybrid parallel genetic algorithm and its application to TSP

Received Date: 2001-04-17
Rev Recd Date: 2001-12-19
Publish Date: 2002-10-19

Abstract

Abstract

This paper applies a multiple population Genetic Algorithm (GA) to solving the TSP (Traveling Salesman Problem). Different populations apply different mutation factors to achieve different search objects. The transition factor among the groups is used to solve the premature convergence problem under some circumstances. It accelerates search process in state space. The experimental results show that this algorithm has great advantage of convergence property over canonical genetic algorithm.

FullText(HTML)

References(1)

References

D.B. Fogel, Evolutionary Computation [M], New York, IEEE Press, 1995, 33-99. ［2］C.K. Mohan, Selective crossover: Towards fitter offspring, Tech. Report SU-EECS TR 97-1,Dept. of EECS, Syracuse University, 1997.[2]B. Yoon, D. J. Holmes, Efficient genetic algorithms for training layered feed forward neural networks, Information Sciences, 1994, 76(1/2), 67-85.[3]J.H. Holland, Adaptation in Natural and Artificial Systems, Michigan University Press, 1975,12-73.[4]玄光男,程润伟,遗传算法与工程设计,北京,科学出版社,2000,1-145.[5]G. Reinelt, TSPLIB; ftp://softlib.rice.edu/pub/tsplib/tsplib/tsplib.tar, 1995.

Relative Articles

Supplements(0)

Cited By

Proportional views