Dynamic Snow Plow Fleet Management under Uncertain Demand and Service Disruption

It is sometimes challenging to plan winter maintenance operations in advance because snow storms are stochastic with respect to, e.g. start time, duration, impact area, and severity. Besides, maintenance trucks may not be readily available at all times due to stochastic service disruptions. A stochastic dynamic fleet management model is developed to assign available trucks to cover uncertain snow plowing demand. The objective is to simultaneously minimize the cost for truck deadheading and repositioning, as well as to maximize the benefits (i.e., level of service) of plowing. The problem is formulated into a dynamic programming model and solved using an approximate dynamic programming (ADP) algorithm. Piece-wise linear functional approximations are used to estimate the value function of system states (i.e., snow plow trucks location over time). The authors apply their model and solution approach to a snow plow operation scenario for Lake County, Illinois. Numerical results show that the proposed algorithm can solve the problem effectively and outperforms a rolling-horizon heuristic solution.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AHD60 Maintenance Equipment. Alternate title: Dynamic Snowplow Fleet Management Under Uncertain Demand and Service Disruption
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Hajibabai, Leila
  • Ouyang, Yanfeng
• Conference:
  • Transportation Research Board 94th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2015-1-11 to 2015-1-15
• Date: 2015

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References; Tables;
• Pagination: 16p
• Monograph Title: TRB 94th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Algorithms; Dynamic programming; Fleet management; Highway maintenance; Service disruption; Snowplows; Stochastic processes; Uncertainty
• Subject Areas: Highways; Maintenance and Preservation; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment; I60: Maintenance; I72: Traffic and Transport Planning; I90: Vehicles;

Filing Info

• Accession Number: 01556414
• Record Type: Publication
• Report/Paper Numbers: 15-1042
• Files: TRIS, TRB, ATRI
• Created Date: Mar 5 2015 5:48PM