Application of Ant Colony Algorithm Based on Optimization Parameters in Equipment Material Transport

Article Preview

Abstract:

In order to solve the path selection problem in the transport of equipment and materials, while improving the quality of solutions, this paper uses ant colony algorithm based on optimization parameters to achieve. Through genetic algorithm to solve the parameters of ant colony algorithm, resulting in a better performance parameters. The experimental results show that ant colony algorithm based on optimization parameters has been improved on path length and computation time than the traditional ant colony algorithm.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

3487-3491

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] B. Bullnheimer, R. F Hartl, C. Strauss. An improved ant system algorithm for the vehicle routing problem[J]. Annals of Operations Research, 1999, 89: 319-328.

DOI: 10.1023/a:1018940026670

Google Scholar

[2] M. Dorigo,V. Maniezzo,A. Colorni. Ant system:optimization by a colony of cooperating agents[J]. IEEE Transactions on Systems,Man,and Cybernetics,1996,26(1):29-41.

DOI: 10.1109/3477.484436

Google Scholar

[3] L. Ma, G. Zhu, A.B. Ning. Ant Colony Optimization Algorithm[M]. Beijing: Science Press, 2008: 10-30.

Google Scholar

[4] H.B. Duan. Ant Colony Algorithm Principle and Its Application[M]. Beijing: Science Press, (2005).

Google Scholar

[5] D.W. Wang, J.W. Wang, H.F. Wang. Intelligent Optimization Method[M]. Beijing: Higher Education Press, (2007).

Google Scholar

[6] J.E. Bell, P.R. McMullen. Ant colony optimization techniques for the vehicle routing problem[J]. Advanced Engineering Informatics, January, 2004, 18(1): 41 -48.

DOI: 10.1016/j.aei.2004.07.001

Google Scholar

[7] S. Mazzeo, I. Loiseau. An ant colony algorithm for the capacitated vehicle routing[J]. Electronic Notes in Discrete Mathematics, December1, 2004, 18, Complete: 181 -186.

DOI: 10.1016/j.endm.2004.06.029

Google Scholar

[8] S.Y. Li. Ant colony algorithm and its application[M]. Harbin: Harbin Institute of Technology Press, (2004).

Google Scholar

[9] S.W. Li, J.Q. Wang, J. W. Zeng. Model of ant colony algorithm parameters optimization based on genetic algorithm[J]. Computer Engineering and Design, 2011, 32(10), 3490-3493.

Google Scholar

[10] M. Tang, E. Ren, C. Zhao. Route Optimization of Bus Dispatching Based on GA-ACA[J]. Microcomputer Information, 2009, 11-1: 48-49.

Google Scholar

[11] M.Q. Li, J.S. Kou, D. Lin, etc. The Basic Theory and Application of Genetic Algorithms[M]. Beijing: Science Press, (2002).

Google Scholar