Assessing the Effects of Limited Curbside Pickup Capacity in Meal Delivery Operations for Increased Safety during a Pandemic

Abstract

Meal delivery has become increasingly popular in past years and of great importance in past months during the COVID-19 pandemic. Sustaining such services depends on maintaining provider profitability and reduced cost to consumers while continuing to support autonomy and independence for customers, restaurants, and delivery drivers (here crowdsourced drivers). This paper investigates the possible enactment of curbside regulations in the U.S. that limit the number of drivers simultaneously waiting at restaurants to pick up meals for delivery on both public safety and delivery efficiency. Curbside regulations would aim to increase safety by enabling social distancing between delivery personnel at pickup locations and have a secondary benefit of improving local traffic flows, which are sometimes impeded in busier, urban locations. Curbside space limits are studied in relation to their impacts on consumer-related performance measures: freshness of the food on delivery and click-to-door time. This investigation is enabled through a proposed hybrid discrete-event and time-advanced simulation platform that replicates meal delivery service calls and pickup and delivery operations across a region built on data from a leading meal delivery company. Embedded within the simulation is an integer program that optimally assigns orders to drivers in a dynamically changing environment. Order assignments are constrained by imposed curbside capacity limits at the restaurants, and potential efficiencies and curbside violation reductions from bundling orders are assessed. Results of analyses from numerical experiments provide insights to state and local communities in designing curbside restrictions that reduce curbside crowding yet enable delivery companies to retain their profitability.