Distributed Robust Chance-Constrained Empty Container repositioning Optimization of the China Railway Express

Abstract

In order to reduce the total cost of empty container repositioning, a multi-period empty container repositioning optimization model of the China Railway Express was established by using distributed robust chance-constrained programming based on partial information such as mean and variance of demand. This established model considered sea-land intermodal transportation, uncertain empty container demand and foldable containers. To simplify the model, the distributed robust chance constraints were transformed into equivalent ones that could be easily solved, and the empty container demands were determined. Numerical experiments were carried out to analyze the influence of different parameters on the total cost. The results showed that the total cost could be greatly reduced by sea-land intermodal transportation. Using foldable containers could reduce the total cost of empty container repositioning. With the improvement of service level, the numbers of empty container repositioning increased owing to the distributional robust chance constraints. When standard and foldable containers were used simultaneously, the total cost could be greatly reduced by appropriately using foldable containers under three different supply–demand relationships of containers. The optimization results may provide a greatly feasible reference for the decision makers of the China Railway Express.