Optimization of Railway Empty Container Repositioning (ECR) with Time Window and Container Type Substitution Based on Genetic Algorithm

ECR is a crucial strategy for enhancing the overall carrying capacity of rail transportation. However, the operational cost is significantly affected by the arrival time of empty containers. When empty containers arrive too early, additional inventory costs are incurred due to idle storage, whereas late arrivals result in opportunity losses. To improve the punctuality of empty container arrival times, this study designs a transportation scheme based on container type substitution. This scheme not only significantly enhances the overall transportation efficiency of the railway system but also further reduces transportation costs. First, a container empty repositioning model based on time windows and container type substitution is constructed. Second, a genetic algorithm is employed to solve the model and determine the optimal substitution strategy. Finally, the effectiveness and unique advantages of the proposed model and algorithm are validated using a case study of a railway freight station with eight container service points. Experimental results demonstrate that the model effectively addresses the ECR problem and yields the optimal repositioning scheme. Under container type substitution, the total cost of ECR is reduced by 11.1% compared to the non-substitution scenario, while inventory costs and opportunity loss costs are reduced by 22.3%. Clearly, container type substitution can lower transportation costs and improve transportation efficiency.