Remote-Meal-Delivery-Data-Repository [supporting dataset]

This report summarizes the results of a 3-month project aimed at coupling artificial intelligence (AI)-based routing and scheduling technology with machine learning to demonstrate an initial solution to the problem of remote delivery of school meals to students in need, and jumpstarting research in this area. With the onset of the COVID-19 pandemic, K-12 school meal programs have been unexpectedly disrupted, raising the need for alternative remote delivery processes. Working together with Allies for Children, a local non-profit organization, and the Penn Hills School District, the authors developed intelligent delivery-location selection along with initial route optimization algorithms and applied them to produce a set of vehicle delivery routes aimed at providing meals to those students in greatest need, while satisfying remote food delivery and social distancing constraints. Delivery vehicles began driving these routes as Penn Hill’s summer school delivery program in July 2020. As of early August, over 5000 school meals have been delivered, and plans are in place to transition this remote meal delivery program into the fall. In this report, the authors summarize the problem, their technical approach and results obtained to date.


  • English

Media Info

  • Media Type: Dataset
  • Dataset publisher:

    Carnegie Mellon University

    Pittsburgh, PA  United States 

Subject/Index Terms

Filing Info

  • Accession Number: 01775952
  • Record Type: Publication
  • Contract Numbers: 69A3551747111
  • Created Date: Jul 6 2021 12:49PM