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Optimization of Winter Maintenance Stations for Safe and Efficient Freight Transportation
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2020-01-01
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Edition:Final Report
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Abstract:Winter maintenance of major transportation corridors in northern states presents a persistent challenge, necessitating substantial investment by Departments of Transportation (DOTs). Inefficient snow removal operations contribute to safety hazards, reduced road capacity, and economic losses, particularly for freight transportation. This study develops a mathematical optimization model to assist DOTs in making both long-term planning and short-term operational decisions for winter maintenance, aiming to enhance snowplow efficiency while minimizing capital and operational costs. The model employs a two-stage stochastic programming approach, integrating priority levels for service regions and stochastic snow event scenarios. The first stage addresses long-term investment decisions, including station locations and fleet acquisition, while the second stage focuses on operational strategies, such as task assignments and de-icing material purchases. The objective function minimizes total costs, including capital investment, operational expenses, and economic losses due to unplowed snow. The solution framework provides optimal station placement, fleet size, resource allocation, and response strategies under varying snow conditions, ensuring robustness against both normal and extreme snow events. Application of the model to Minnesota’s winter maintenance system reveals key insights: as annual snow events increase, operational costs comprise a larger share of total expenses; additional stations become necessary to mitigate transportation costs and economic losses from unplowed snow; for typical conditions with 30 snow events per year, the estimated total cost is $27.5 million, with 43 stations, 87 service regions, and a fleet size of 300; extreme snow events require significantly expanded resources, with 54 stations and a fleet of 475 trucks. Notably, prioritization based on general traffic volume versus heavy-commercial vehicle volume does not yield substantial differences in optimal decisions. This decision support system offers DOTs a financially efficient tool for winter maintenance planning, reducing costs while improving operational effectiveness. Implementation of the proposed model enhances the safety and efficiency of freight transportation during winter, ultimately benefiting the broader transportation network.
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[PDF-1.97 MB]
