Student Competition Poster Winner, Fateme Hafizi: Permanent/Mobile Combined Charging Stations for a Drone-based Delivery Network Under Uncertain Demand
Student: Fateme Hafizi, PhD student, Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology
Urban freight transportation results in traffic congestion and air pollution. Consequently, freight shippers are increasingly interested in using drones as environmentally friendly alternatives for delivery. However, cargo drones face limitations due to their short flying ranges. A practical solution to this issue is to deploy charging infrastructure to extend drone range. This paper proposes a new framework for the optimal deployment of electric charging stations for drones across urban networks. Given the inherent demand uncertainty in urban freight delivery, which can vary significantly from day to day and across different daily time periods, it necessitates including mobile charging stations moving through the network in addition to permanent charging stations. A two-stage mixed-integer optimization model is proposed to determine the optimal combination of permanent and mobile charging stations to maximize demand fulfillment by drone-based delivery services, capturing the uncertainty in parcel delivery demand. The optimization formulation explicitly considers urban parcel delivery network characteristics, demand uncertainty, and budget constraints. This formulation is NP-hard and difficult to solve. Hence, the model utilizes decomposition in conjunction with branch and bound or genetic algorithm to derive optimal solutions efficiently. The proposed framework is applied to a case study of San Francisco County, California. The findings indicate that the integration of mobile charging stations significantly enhances the system to serve high-demand areas under uncertain demand scenarios. Additionally, the placement strategy supports efficient drone operations and offers valuable insights for improving urban logistics and service reliability.