MPC Research Reports |
Title: | Assessing and Improving Efficiency of Snowplowing Operations via Data and Analytics |
Authors: | Cathy Liu and Nikola Markovic |
University: | University of Utah |
Publication Date: | Nov 2022 |
Report #: | MPC-22-487 |
Project #: | MPC-637 |
TRID #: | 01892557 |
Keywords: | data analysis, performance measurement, routes and routing, snowplows, snow removal, travel time, visualization |
This project presents a comprehensive study on enhancing snowplowing routes in 12 regions in northern Utah. The research employs both exact and approximate methods to identify snowplowing routes that lead to reductions in total travel time, turnaround time, and deadhead miles by an average of 4.87%, 15.38%, and 13.85%, respectively, across all the regions. These improvements can significantly enhance the efficiency of snow removal operations and contribute to the overall social welfare. The study's models also examine the tradeoffs between various operational policies, such as echelon vs. non-echelon routing and fleet extension. These insightful analyses empower local management teams to determine the most suitable strategies for their respective regions. Apart from optimization modeling, a pivotal aspect of this work involves data visualization. The team utilizes data visualization techniques to effectively demonstrate the efficacy of the new snowplowing routes, comparing them to current practices, and presenting the findings to the Utah Department of Transportation. This visualization aids in conveying the significance and impact of the proposed improvements, further supporting decision-making processes.
Liu, Cathy, and Nikola Markovic. Assessing and Improving Efficiency of Snowplowing Operations via Data and Analytics, MPC-22-487. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2022.