中断下多式联运网络中多品类货运的路径规划模型
Routing Model for Multicommodity Freight in an Intermodal Network under Disruptions
AI总结：
本研究针对中断下多式联运多品类货运路径问题，构建随机混合整数规划模型并采用样本平均近似算法求解，经两类网络验证，得出公铁联运更适配中断场景且模型生成路径鲁棒性更优的结论。
摘要：
本文提出了一种中断场景下多式联运网络中多品类货运路径规划的数学模型。研究构建了一个随机混合整数规划模型，其优化目标不仅是最小化多种运输方式的运营成本与枢纽转运成本，还包括与未满足需求相关的惩罚成本。研究采用样本平均近似算法求解这一具有挑战性的问题。 随后，研究将所构建的模型应用于两个网络——一个假设的15节点网络，以及美国墨西哥湾沿岸、东南部和中大西洋地区的实际多式联运网络，以验证模型的适用性，且模型明确考虑了链路、节点和枢纽处的中断情况。模型结果表明，发生中断时，由于货运运输网络具备内置冗余性，研究区域内的货物应通过公铁多式联运网络运输。此外，研究发现该模型生成的路径比货运运营商通常使用的路径更具鲁棒性。
英文摘要：
This paper presents a mathematical model for the routing of multicommodity freight in an intermodal network under disruptions. A stochastic mixed-integer program was formulated to minimize not only operational costs of various modes and transfer costs at terminals but also penalty costs associated with unsatisfied demands. The sample average approximation algorithm was used to solve this challenging problem. The developed model was then applied to two networks-a hypothetical 15-node network and an actual intermodal network in the Gulf Coast, Southeastern, and Mid-Atlantic regions of the United States-to demonstrate its applicability with explicit consideration of disruptions at links, nodes, and terminals. The model results indicated that during disruptions, goods in the study region should be shipped by road-rail intermodal network because of the built-in redundancy of the freight transport network. Additionally, the routes generated by the model were found to be more robust than those typically used by freight carriers.
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