Tactical Production and Distribution Planning in Urban Logistics under Vehicle Operational Restrictions

Significant uncertainty associated with Chinese urban logistics, caused by random vehicle operational restrictions due to severe weather (e.g., smog) in addiction to normal traffic variation makes the tactical production and distribution planning decisions quite challenging. In this paper, we propose a two-stage stochastic integer programming model for an optimal production distribution capacity planning problem under the aforementioned uncertainties. We aim to minimize both procurement spending and the expected operational cost under logistic uncertainty. Given the computational burden of solving the resultant stochastic integer program for real-world instances, we develop an improved stochastic branch-and-bound (SBB) algorithm embedding with Tabu search method. We conduct the numerical study to verify the superiority of the proposed algorithm. We also offer managerial insights to practitioners and policy recommendations to municipal governments based on the numerical study results.