4.6 Article

Managing rail-truck intermodal transportation for hazardous materials with random yard disruptions

期刊

ANNALS OF OPERATIONS RESEARCH
卷 309, 期 2, 页码 457-483

出版社

SPRINGER
DOI: 10.1007/s10479-020-03699-1

关键词

Hazardous materials; Rail-truck intermodal transportation; Robust optimization; Reliability; Yard disruption

资金

  1. Natural Sciences and Engineering Research Council of Canada [RGPIN-2015-04013]

向作者/读者索取更多资源

This study develops a scenario-based robust optimization model for rail-truck intermodal transportation network in the presence of disruptions. By proposing recovery mechanisms and additional constraints, considering different disruption scenarios, the study minimizes expected risk and variability to ensure network reliability. Numerical experiments and sensitivity analyses reveal the relationship between system robustness, reliability, and provide managerial insights for disruption management.
Combining multiple transportation modes, intermodal transportation has been widely used in shipping hazardous materials (hazmat). But the relevant research on intermodal transportation for hazmat is still limited, especially when the planning environment contains possible system disruptions. This study develops a scenario-based robust optimization model for a rail-truck intermodal transportation network that ships regular and multiple hazmat freights with random disruptions at intermodal yards. To be specific, three operational level and one strategic level recovery mechanisms are proposed to maintain network connectivity during disruptions. Then, embedding various yard disruption scenarios with recovery plans, the expected risk and corresponding variability are minimized simultaneously, considering an additional augmented constraint to ensure the reliability in cost. Numerical experiments based on a real-world intermodal network of CSX, a leading rail-based freight transporter in North America, are conducted to find the optimal robust network structure and routing plan. A series of sensitivity analyses, in terms of recovery mechanisms and key parameter values, reveal relationships among the robustness and reliability of the intermodal transportation system. Further managerial insights can be used to assist intermodal carrier in seeking contingency plans for disruptions.

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