ISE seminar

Title: Capacity planning in food delivery platforms with autonomous vehicles (AV): Role of delivery-time guarantee

Speaker

Dr. Neda Mirzaeian: Assistant Professor, The University of Texas at Dallas

Abstract

We investigate optimal staffing and pricing strategies for a food delivery platform that utilizes both human drivers and autonomous delivery vehicles (ADVs) under a delivery time guarantee. Our study focuses on minimizing operational costs through an optimization problem, revealing nuanced interplays between drivers’ wages, vehicle wear and tear, ADV leasing costs, and ADV capacity. First, the optimal ADV capacity size is determined as a long-term strategic decision, influencing the choice of ADV supplier for the platform. The feasibility and optimal number of resources, including both ADVs and human drivers, are then compared to a benchmark relying solely on human drivers. Additionally, the potential for ADVs to fully replace human drivers in the food delivery industry is analyzed. Our findings suggest that optimal resource allocation often requires the simultaneous use of both human drivers and ADVs, as their integration enhances feasibility and efficiency. Our numerical analysis shows that adding 50 ADVs—a relatively small number for a 28-square-mile city—replaces 57 crowd-sourced drivers (a 12% reduction in the number of resources employed) while leading to a 6% cost savings for the platform. Additionally, we explore strategic staffing and pricing for a periodic demand scenario (i.e., non-peak and peak demand periods). The results emphasize the necessity of a hybrid fleet, with human drivers remaining crucial in the near future. Our findings offer valuable insights for food delivery platforms, ADV suppliers, and human drivers, assisting in optimal resource deployment and providing foresight into the evolving landscape of food delivery services.

Bio

Dr. Neda Mirzaeian is an Assistant Professor of Operations Management at the Jindal School of Management, University of Texas Dallas. She earned her PhD in Operations Management from the Tepper School of Business, Carnegie Mellon University. Neda's research is primarily centered on smart city operations, with a specialized focus on examining the impact of advanced technologies, such as autonomous vehicles, on critical urban infrastructure and services. Her work delves into the intricate dynamics of highway traffic congestion, parking systems, and delivery services within urban environments. Furthermore, she actively explores innovative research avenues at the crossroads of operations management and sustainability.