An Efficient Real-Time Railway Container Yard Management Method Based on Partial Decoupling

Sea-rail intermodal transportation is an essential infrastructure in global supply chains nowadays. Since the yard is the interface between sea and land, optimizing the transportation process in yards is of significant interest for increasing transportation efficiency. However, the yard management problem usually suffers from the large state space and cannot be solved effectively. We consider this important problem from a decomposition perspective, focusing on real-time scheduling in railway container yards, and make the following contributions. We show the partial decomposition property of the yard management problem. This property establishes the equivalence between joint optimization of yard components and independent optimization of each component under mild assumptions, achieving optimality and effectiveness simultaneously. Utilizing this property, we further simplify each subproblem while preserving the optima, and develop algorithms for each simplified subproblem. Numerical experiments demonstrate the performance of proposed algorithms and the contribution of optimizing each subproblem from various perspectives. Note to Practitioners—Yard is the interface between sea and land in sea-rail intermodal transport, thus being the bottleneck of the transport efficiency. Optimizing yard management is important but challenging, since the matching between trains and yards, the allocation of yard storage, and the movement of cranes should be jointly optimized, which compose a complex problem with an exponentially large decision space. Besides, as modifications to already-deployed systems always come with significant costs, improving transport efficiency with minimal adjustments is significant, which emphasizes the importance of identifying the most crucial component. We address these difficulties in this work and show that train matching, yard storage allocation, and crane scheduling can be decoupled under mild assumptions. To utilize the partial decomposition property, algorithms for each subproblem are further proposed respectively, the effectiveness of which is shown in numerical simulation. And the contribution of optimizing each sub-problem is compared, which provides valuable rule-of-thumb for practice.