Title :
Application of the important sampling method to Vehicle Routing Problem with weight coefficients and Stochastic Demands
Author_Institution :
Inf. Coll., Capital Univ. of Economic & Bus., Beijing, China
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;
Conference_Titel :
Control and Automation (ICCA), 2010 8th IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-5195-1
Electronic_ISBN :
1948-3449
DOI :
10.1109/ICCA.2010.5524427