Vehicle Routing Problem Based on Particle Swarm Optimization Algorithm with Gauss Mutation
American Journal of Software Engineering and Applications
Volume 5, Issue 1, February 2016, Pages: 1-6
Received: Nov. 30, 2015; Accepted: Dec. 10, 2015; Published: Dec. 25, 2015
Views 4176      Downloads 189
Authors
Ting Xiang, College of Mathematic and Information, China West Normal University, Nanchong, China
Dazhi Pan, College of Mathematic and Information, China West Normal University, Nanchong, China
Haijie Pei, College of Mathematic and Information, China West Normal University, Nanchong, China
Article Tools
Follow on us
Abstract
In order to solve the vehicle routing problem, this paper introduces the Gauss mutation, which is based on the common particle swarm algorithm, to constitute an improved particle swarm algorithm (NPSO). In the process of solving vehicle routing problem, the NPSO is encoded by integer and proposes a new way to adjust the infeasible solutions. The particles are divided into two overlapping subgroups, and join the two-two exchange neighborhood search to iterate. Finally, the simulation experiments show that the proposed algorithm can get the optimal solution faster and better, and it has a certain validity and practicability.
Keywords
Particle Swarm Optimization, Vehicle Routing Problem, Gauss Mutation, Neighborhood Search
To cite this article
Ting Xiang, Dazhi Pan, Haijie Pei, Vehicle Routing Problem Based on Particle Swarm Optimization Algorithm with Gauss Mutation, American Journal of Software Engineering and Applications. Vol. 5, No. 1, 2016, pp. 1-6. doi: 10.11648/j.ajsea.20160501.11
Copyright
Copyright © 2015 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Jun Li, Yaohua Guo. Theory and method of logistics distribution vehicle scheduling [M]. Beijing: China material press, 2001.
[2]
Laporte G. The vehicle routing problem: an overview of exact and approximation algorithms [J]. European Journal of operational Research, 1992, 5(9): 345一358.
[3]
Hongchun HU, Yaohua WU, Li LIAO. Optimization and application of logistics distribution vehicle [J]. Journal of Shandong University (Engineering Science), 2007, 37(4): 104-107.
[4]
Eberhart R, Kennedy J. A new optimizer using particle swarm theory [A]. Proceedings of the International Symposium on Micro Machine and Human Science [C]. Piscataway, NJ, USA: IEEE, 1995: 39-43.
[5]
Kennedy J, Eberhart R. Particle swarm optimization [A]. Proceedings of the IEEE International Conference on Neural Networks [C]. Piscataway, NJ, USA: IEEE, 1995: 1942-1948.
[6]
Zhen Huang. Hybrid quantum Particle Swarm Optimization algorithm for vehicle routing problem [J]. Computer Engineering and Applications, 2013. 49(24): 219-223.
[7]
Dongqing Ma, Wei Wang. Logistics distribution vehicle scheduling based on improved particle swarm optimization [J]. Computer Engineering and Applications, 2014, 50(11): 246-270.
[8]
Yaohua Wu, Nianzhi Zhang. Modified Particle Swarm Optimization algorithm for vehicle routing problem with time windows [J]. Computer Engineering and Applications, 2010, 46(15): 230-234.
[9]
Ya Li, Dan Li, Dong Wang. Improved chaos particle swarm optimization algorithm for vehicle routing problem [J]. Application Research of Computers, 2011, 28(11): 4107-4110.
[10]
Ning Li, Tong Zou. Particle swarm optimization for vehicle routing problem [J]. Journal of Systems Engineering, 2004, 19(6): 596-600.
[11]
Bing Wu. Research and application of particle swarm optimization algorithm for vehicle routing problem [D]. Zhejiang University of Technology, 2008.
[12]
Yuanbing Mo, Fuyong Liu. Artificial glowworm swarm optimization algorithm with Gauss mutation [J]. Application Research of Computers, 2013, 30(1): 121-123.
[13]
Xing Liu, Guoguang He. Study on tabu search algorithm for stochastic vehicle routing problem [J]. Application Research of Computers, 2007, 43(24): 179: 181.
ADDRESS
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
U.S.A.
Tel: (001)347-983-5186