Optimization of Winter Maintenance Stations for Safe and Efficient Freight Transportation

Principal Investigator(s):

Alireza Khani, Assistant Professor, Civil, Environmental and Geo-Engineering


  • John Hourdos, Former Research Associate Professor, Civil, Environmental and Geo-Engineering

Project summary:

In the northern states, winter maintenance of major transportation corridors is an ongoing issue. Apart from the general cost to the traveling public, freight transport has additional economic considerations, as well as operational and safety characteristics. The effect of winter maintenance operations and severe weather conditions on freight fluidity has not been adequately investigated. Specifically, efficient planning and operations of stations--where trucks, snowplows, and other road machinery as well as deicing materials are maintained in and dispatched from--can significantly improve the cost-effectiveness of the operations. In the state of Minnesota, most of the truck stations are reaching their life expectancy and need to be reconstructed or relocated in a multi-period plan. An efficient plan starts with optimization of stations' location, type, and size, followed by vehicle routing and scheduling for snow plowing and salt distribution on roads, to facilitate safe and efficient freight transport in winter, with minimum operations cost.

This project will study the freight fluidity challenges in winter and how to optimize winter road maintenance operations for better freight transportation. Researchers will develop an optimization model for finding the optimal location of stations for new construction or capacity expansion, considering desired service quality for major freight corridors, followed by assignment of stations and trucks to service zones. Two key aspects of the study that distinguishes it from regular station location optimization are: 1) determining the freight volume on the state road network and determining critical links or zones for prioritized maintenance, and 2) accounting for stochastic model parameters, e.g. snowfall amount and storm duration, and employing robust optimization to design reliable service for extreme conditions. A decision support system will be developed based on mathematical programming and road network topology in GIS. The decision support system could benefit agencies from a financial perspective by reducing the winter maintenance operations cost, and the freight industry by safe and efficient freight transport in winter. Any software tool created in this research will be shared with local agencies and research community in open source format.

Project details:

  • Project number: 2019066
  • Start date: 11/2018
  • Project status: Completed
  • Research area: Transportation Safety and Traffic Flow