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Optimization of Snowplow Routes for Real-World Conditions

Author

Listed:
  • Abdullah Rasul

    (Department of Automotive and Mechatronics Engineering, Ontario Tech University, 2000 Simcoe Street North, Oshawa, ON L1G 0C5, Canada)

  • Jaho Seo

    (Department of Automotive and Mechatronics Engineering, Ontario Tech University, 2000 Simcoe Street North, Oshawa, ON L1G 0C5, Canada)

  • Shuoyan Xu

    (Department of Civil and Environmental Engineering, University of Alberta, 116 St. & 85 Ave., Edmonton, AB T6G 2R3, Canada)

  • Tae J. Kwon

    (Department of Civil and Environmental Engineering, University of Alberta, 116 St. & 85 Ave., Edmonton, AB T6G 2R3, Canada)

  • Justin MacLean

    (Office of the Chief Administrative Officer, Municipality of Clarington, 40 Temperance Street, Bowmanville, ON L1C 3A6, Canada)

  • Cody Brown

    (Office of the Chief Administrative Officer, Municipality of Clarington, 40 Temperance Street, Bowmanville, ON L1C 3A6, Canada)

Abstract

During the winter season, snowplowing has a significant effect on road users as it is critical to winter road maintenance and operations. The main goal of this study is to generate optimal routes for snowplowing trucks for efficient road maintenance. In addition to the conventional problem of reducing travel time and distance, this study also incorporates actual operational constraints, such as minimum maintenance standards and driver safety, to improve the overall efficiency of operations. To achieve the objectives, we first implemented the Chinese Postman Problem (CPP) to create Euler circuits from the initial routes and then identified the shortest paths by applying Dijkstra’s algorithm. Then, the Tabu search algorithm was chosen as a metaheuristic algorithm for the optimization process that finds near-optimal solutions by considering operational constraints for snowplow routes. Unsafe turning conditions and minimum maintenance standards were taken into account in the objective function defined for the optimization process. In simulations, the route obtained by our approach was compared to one with the application of CPP only in terms of travel distance, time, turning conditions, and road maintenance priority.

Suggested Citation

  • Abdullah Rasul & Jaho Seo & Shuoyan Xu & Tae J. Kwon & Justin MacLean & Cody Brown, 2022. "Optimization of Snowplow Routes for Real-World Conditions," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13130-:d:941165
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    References listed on IDEAS

    as
    1. Nathalie Perrier & André Langevin & Ciro-Alberto Amaya, 2008. "Vehicle Routing for Urban Snow Plowing Operations," Transportation Science, INFORMS, vol. 42(1), pages 44-56, February.
    2. Malandraki, Chryssi & Daskin, Mark S., 1993. "The maximum benefit Chinese postman problem and the maximum benefit traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 65(2), pages 218-234, March.
    3. Sullivan, James L. & Dowds, Jonathan & Novak, David C. & Scott, Darren M. & Ragsdale, Cliff, 2019. "Development and application of an iterative heuristic for roadway snow and ice control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 18-31.
    4. Korteweg, Peter & Volgenant, Ton, 2006. "On the Hierarchical Chinese Postman Problem with linear ordered classes," European Journal of Operational Research, Elsevier, vol. 169(1), pages 41-52, February.
    5. Fred Glover, 1990. "Tabu Search: A Tutorial," Interfaces, INFORMS, vol. 20(4), pages 74-94, August.
    6. Edward Minieka, 1979. "The Chinese Postman Problem for Mixed Networks," Management Science, INFORMS, vol. 25(7), pages 643-648, July.
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