The Research on VRP Based on Max-Min Ant Colony Algorithm

Article Preview

Abstract:

Vehicle routing problem (VRP) is the key to reducing the cost of logistics, and also an NP-hard problem. Ant colony algorithm is a very effective method to solve the VRP, but it is easy to fall into local optimum and has a long search time. In order to overcome its shortcomings, max-min ant colony algorithm is adopted in this paper, and its simulation system is designed in GUI of MATLAB7.0. The results show that the vehicle routing problem can well achieves the optimization of VRP by accessing the simulation data of database.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 219-220)

Pages:

1285-1288

Citation:

Online since:

March 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Dorigo M, Gambar D. Ant colony algorithm for the traveling salesman problems in biological systems. IEEE Transactions on Evolutionary Computation, Vol.43 (1997), pp.73-81.

Google Scholar

[2] Haibin Duan. Principle and Application of Ant Colony Algorithm. Beijing: Science press (2005.12).

Google Scholar

[3] Gang Zhao, Wenjuan Luo, Ruoying Sun and ChunhuaYin. A modified max-min ant system for vehicle routing problems. International Conference on Wireless Communications, Networking and Mobile Computing (2008).

DOI: 10.1109/wicom.2008.1507

Google Scholar

[4] Rongwen Zhang and Shaomei Zhou. The application of the improved hybrid ant colony algorithm in vehicle routing optimization problem. Proceedings of the 2010 2nd International Conference on Future Computer and communication, ICFCC (2010).

DOI: 10.1109/icfcc.2010.5497706

Google Scholar

[5] Tao Zhang, Chuoya Yu, Wenxin Tian. Ant Colony system based on the asrank and mmas for the VRPSPD. International Conference on Wireless Communications, Networking and Mobile Computing (2007), pp.3723-3726.

DOI: 10.1109/wicom.2007.922

Google Scholar

[6] Chen Qi, Ning Bo. The application of vehicle route problem with time windows based on MMAS. Jiangsu University of science and technology journal (Natural science edition), vol.23 (2009), pp.263-266.

Google Scholar

[7] Jun MA, Yu Zhang, Jianpei Zhang. Solution to traveling agent problem based on improved ant colony algorithm. International Colloquium on Computing, Communication, Control and Management, ISECS, (2008), pp.57-60.

DOI: 10.1109/cccm.2008.317

Google Scholar

[8] Rongwen Zhang, Shaomei Zhou. The Application of The Improved Hybrid Ant Colony Algorithm in Vehicle Routing Optimization Problem. Proceeding of the 2010 2nd International Conference on Future Computer and Communication, ICFFCC (2010).

DOI: 10.1109/icfcc.2010.5497706

Google Scholar