Optimization of Distribution Routing Problem Based on Travel Time Reliability

Author

Jie Gao

Author_Institution

Liaocheng Univ., Liaocheng, China

Volume

1

fYear

2009

fDate

26-27 Dec. 2009

Firstpage

19

Lastpage

22

Abstract

As part of solutions to the technical problem of logistics distribution, vehicle routing problem (VRP) is getting more and more attention in academics and enterprises, it belongs to the NP-hard problem theoretically. VRP with time windows and capacity constraint in stochastic traffic network was studied based on travel time reliability . Firstly, travel time was expressed as a random variable according to previous collected data, and travel time reliability was obtained using the Monte-Carlo method. Then multi-objective optimization model satisfying travel time reliability constrain as well as multi-objective chance-constraints was presented for optimization of distribution routing, and modified genetic algorithm for the model was proposed. At last, numerical results were provided to demonstrate the feasibility and validity of the proposed model and algorithm.

Keywords

Monte Carlo methods; computational complexity; genetic algorithms; goods distribution; logistics; stochastic processes; Monte-Carlo method; NP-hard problem; capacity constraint; distribution routing problem optimisation; logistics distribution; modified genetic algorithm; multiobjective chance-constraints; multiobjective optimization model; stochastic traffic network; time windows; travel time reliability; vehicle routing problem; Constraint optimization; Logistics; NP-hard problem; Random variables; Routing; Stochastic processes; Telecommunication traffic; Time factors; Traffic control; Vehicles; genetic algorithm; logistics distribution; stochastic traffic network; travel time reliability; vehicle routing problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Management, Innovation Management and Industrial Engineering, 2009 International Conference on

Conference_Location

Xi´an

Print_ISBN

978-0-7695-3876-1

Type

conf

DOI

10.1109/ICIII.2009.11

Filename

5369874