Application of the important sampling method to Vehicle Routing Problem with weight coefficients and Stochastic Demands

Author

Qiu, Yue

Author_Institution

Inf. Coll., Capital Univ. of Economic & Bus., Beijing, China

fYear

2010

fDate

9-11 June 2010

Firstpage

1207

Lastpage

1210

Abstract

Vehicle Routing Problem has been approved a NP problem and it belongs to classical Combination Optimization hard problem. An effective algorithm based on Important Sampling is designed to solve the model which named Vehicle Routing Problem with Weight Coefficients and Stochastic Demands (WVRPSD). The optimal importance sampling distribution function was obtained by making use of the expection constructed by likelihood ratio. Numerical experiments have been conducted and the results indicate that the method can effectively solve this problem.

Keywords

combinatorial mathematics; computational complexity; optimisation; stochastic processes; vehicles; NP problem; combination optimization hard problem; likelihood ratio; optimal importance sampling distribution function; stochastic demands; vehicle routing problem; weight coefficients; Automatic control; Costs; Fuel economy; Monte Carlo methods; NP-hard problem; Routing; Sampling methods; Stochastic processes; Transportation; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation (ICCA), 2010 8th IEEE International Conference on

Conference_Location

Xiamen

ISSN

1948-3449

Print_ISBN

978-1-4244-5195-1

Electronic_ISBN

1948-3449

Type

conf

DOI

10.1109/ICCA.2010.5524427

Filename

5524427