An importance sampling method with applications to vehicle routing problem

Abstract

Vehicle routing problem belongs to classical Combination Optimization hard problem and has been extensively studied by many researchers. The main purpose of this paper is to establish the model which named Vehicle Routing Problem with Weight Coefficients and Stochastic Demands (WVRPSD) and propose an effective algorithm based on Important Sampling to solve this model. The optimal importance sampling distribution function was obtained by making use of the martingale constructed by likelihood ratio. Numerical experiments have been conducted and the results indicate that the method can effectively solve this problem.