What is the Optimal Fleet Size for Online Food Delivery Companies?– An Application to San Francisco

The introduction of the gig-economy led to the rapid growth of the online food market. During the outbreak of the Covid-19, online food delivery is considered a new solution to restaurant operations and accelerating the growth of the industry. However, there has been little discussion about how best to size and operate a fleet of vehicles, given the increasing demand for online food delivery. The authors provide a graph theory-based solution to the optimized fleet size problem to serve all the delivery demands without any delay in an autonomous driving setting. The authors tested the solution based on different operational scenarios to estimate the trade-off between transportation performance (VMT and VHT) and fleet size for deliveries. The authors used a dataset of Eat24.com delivery records taken in the city of San Francisco between April 17 and April 30 in 2017. The algorithm allows each delivery vehicle to serve daily 29 deliveries on average (52 vehicles for 1508 deliveries per day) when maximizing the reduction in fleet size. Although incorporating human driver constraints and stacked order option may lead to a different value for the fleet size, the authors expect our result could provide insights to delivery service operators and policymakers who are concerned about the operational, social, and environmental impacts of urban logistics.

• Record URL:
  • https://annualmeeting.mytrb.org/OnlineProgram/Details/15506
• Supplemental Notes:
  • This paper was sponsored by TRB committee AT030 Standing Committee on Agriculture and Food Transportation.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Park, Bumsub
  • Saphores, Jean-Daniel M
• Conference:
  • Transportation Research Board 100th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2021-1-5 to 2021-1-29
• Date: 2021

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 17p

Subject/Index Terms

• TRT Terms: Algorithms; Delivery service; Electronic commerce; Fleet management; Food service; Vehicle fleets
• Geographic Terms: San Francisco (California)
• Subject Areas: Economics; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01763805
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-03465
• Files: TRIS, TRB, ATRI
• Created Date: Feb 4 2021 10:57AM