Wang Qiuyun
School of Information Management, Beijing Information Science and Technology University, Beijing, 100192, China
Jiang Wenbao
School of Information Management, Beijing Information Science and Technology University, Beijing, 100192, China
Zhao Gang
School of Information Management, Beijing Information Science and Technology University, Beijing, 100192, China
ABSTRACT
For it is very difficult and complex to solve large-scale dynamic vehicle routing problem on distribution goods, propose the multi-objective optimization Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) model for distribution goods, which maximizes the number of customer serviced, minimizes customer waiting time and the total vehicle driving distance and covers dynamic information both random demand and dynamic network. Then a two stage algorithm model based on hill-climbing and genetic hybrid algorithm is designed to solving DVRPTW. At last, we do the simulation experiment with standard test data from Solomon and the result shows that this model and algorithm is quite capable of solving the dynamic vehicle routing problem on distribution goods.
PDF References Citation
Received: June 02, 2013;
Accepted: October 09, 2013;
Published: November 16, 2013
How to cite this article
Wang Qiuyun, Jiang Wenbao and Zhao Gang, 2013. A Novel Model and Algorithm for Solving Dynamic Vehicle Routing Problem on Goods Distribution. Journal of Applied Sciences, 13: 5410-5415.
DOI: 10.3923/jas.2013.5410.5415
URL: https://scialert.net/abstract/?doi=jas.2013.5410.5415
DOI: 10.3923/jas.2013.5410.5415
URL: https://scialert.net/abstract/?doi=jas.2013.5410.5415
REFERENCES
- Fleischmann, B., S. Gnutzmann and E. Sandvo, 2004. Dynamic vehicle routing based on online traffic information. Trans. Sci., 38: 420-433.
CrossRefDirect Link - Branke, J., M. Middendorf, G. Noeth and M. Dessouky, 2005. Waiting strategies for dynamic vehicle routing. Transp. Sci., 39: 298-312.
CrossRefDirect Link - Chen, Z.L. and H. Xu, 2006. Dynamic column generation for dynamic vehicle routing with time windows. Trans. Sci., 40: 74-88.
CrossRefDirect Link - Lu, L. and Q.M. Tan, 2006. Hybrid particle swarm optimization algorithm for stochastic vehicle routing problem. Syst. Eng. Electron., 28: 244-247.
Direct Link - Liu, S.X. and H.L. Feng, 2008. Optimization approach to solving dynamic vehicle routing problems. J. Northeastern Univ. (Nat. Sci.), 29: 484-487.
Direct Link