A research based on K-means clustering and Artificial Fish-Swarm Algorithm for the Vehicle Routing Optimization

Author

Ji De-gang ; Huang Dong-mei

Author_Institution

Coll. of Sci., Agric. Univ. of Hebei, Baoding, China

fYear

2012

fDate

29-31 May 2012

Firstpage

1141

Lastpage

1145

Abstract

Vehicle Routing Problem (VRP) is an important problem in logistic system. Because of its NP-hard property, it is difficult to get the optimal solution when the constrains are more. Aiming at the problem of logistics distribution vehicle routing optimization, this paper provide a composite algorithm based on the K-means clustering and the Artificial Fish-Swarm Algorithm for the vehicle routing optimization (KMAFA). The results indicate that the algorithm can reduce the input of the algorithm and improve the converging speed. The computational result shows that the results of composite algorithm for VRP are competitive.

Keywords

goods distribution; logistics; optimisation; pattern clustering; transportation; KMAFA; NP hard property; VRP; k-means clustering and the artificial fish-swarm algorithm; logistic system; logistics distribution vehicle routing optimization; optimal solution; Classification algorithms; Clustering algorithms; Heuristic algorithms; Logistics; Optimization; Routing; Vehicles; AFSA; KMAFA; the K-means clustering; the VRP;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2012 Eighth International Conference on

Conference_Location

Chongqing

ISSN

2157-9555

Print_ISBN

978-1-4577-2130-4

Type

conf

DOI

10.1109/ICNC.2012.6234729

Filename

6234729