A two-stage stochastic programming with recourse model for cross-border distribution with fleet management

Abstract

One of the significant effects of the implementation of an open-door policy in China is that many Hong Kong-based manufacturers’ production lines have been moved to China to take advantage of the lower production costs, lower wages and lower rental costs, but as a consequence the finished products must be delivered from China to Hong Kong. It has been discovered that, given a noisy set of data, distribution management cannot determine an appropriate strategy, and hence unnecessarily high expenditure is being incurred. In this paper, a stochastic linear programming model is developed to solve cross-border distribution problems in an environment of uncertainty. Under different economic growth scenarios, decision-makers can determine a long-term distribution strategy, including the optimal delivery routes and the optimal vehicle fleet composition. A set of data from a Hong Kong-based manufacturing company is used to demonstrate the robustness and effectiveness of our model. The analysis of two possible changes in distribution strategies is also considered. The proposed model can provide appropriate distribution strategy with fleet management in an uncertain environment.