Algorithm study of multiple-depot vehicle routing problem based on fuzzy simulation

Author

Li-xia, Rong

Author_Institution

Comput. Dept., Dezhou Univ., Dezhou, China

fYear

2009

fDate

15-16 May 2009

Firstpage

184

Lastpage

187

Abstract

In this paper, the multiple-depot vehicle routing problem with fuzzy demands is considered, on the basis of uncertain demand of multiple-depot vehicle routing problem, a fuzzy chance constrained program is designed based on fuzzy credibility theory. Then the hybrid genetic algorithm based on fuzzy simulation is used to solve the vehicle routing model. In genetic algorithm, a new code is given, and introduce an evolution method that combining evolution of same depot vehicle and different depot vehicle, in order to avoid local constringency and get general optimization. The results of experiment indicated that the algorithm can effectively solve the fuzzy vehicle routing problem.

Keywords

combinatorial mathematics; fuzzy set theory; genetic algorithms; simulation; transportation; vehicles; combinatorial optimization problem; evolutionary method; fuzzy chance constrained program design; fuzzy credibility theory; fuzzy demand; fuzzy multiple-depot vehicle routing problem; fuzzy simulation; hybrid genetic algorithm; transportation problem; Computer industry; Constraint theory; Costs; Genetic algorithms; Optimization methods; Possibility theory; Routing; Transportation; Uncertainty; Vehicles; fuzzy credibility; fuzzy simulation; fuzzy vehicle routing problem; hybrid genetic algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-3817-4

Type

conf

DOI

10.1109/ICIMA.2009.5156591

Filename

5156591