Dear faculty members and fellow students,
You are cordially invited to attend my upcoming thesis defense.
Title: Innovations in Last-Mile Delivery Systems
Advisors: Dr. Alan Erera, Dr. Martin Savelsbergh
Dr. Basak Kalkanci (Scheller College of Business)
Dr. Andy Sun
Dr. Alejandro Toriello
Date and time: Wednesday, December 13th, 10:30 AM
Location: ISyE Main Building 228
In the last decade, tied to the rise of e-commerce activities, direct-to-consumer delivery operations have grown at a rapid pace in metropolitan areas across the world, and expectations on service standards become higher and higher every year. The economic, social and environmental sustainability of last-mile logistical operations poses a formidable societal challenge, demanding major organizational changes and technological inventions in transportation, the success of which will critically depend on the availability of appropriate optimization tools.
In this thesis, we study two recent innovations in last-mile delivery: i) roaming delivery systems, where the orders are delivered to the trunk of a customer’s cars, as opposed to a static location like home; and ii) dynamic delivery systems, where vehicles deliver goods locally from an origin depot (or, perhaps a small number of origin depots) to customer locations, and the requests for delivery arise during the vehicle operating period, which, if accepted, must be satisfied within a service window (e.g., meal delivery) or by the end of the day (e.g., same-day delivery).
We introduce the vehicle routing problem with roaming delivery locations and the meal delivery routing problem, to formalize and conduct a systematic study of the essential features of these systems, and then develop heuristics and optimization-based tools that enable their successful deployment. On a more basic level, we contribute to the understanding of the relation between cost and service quality objectives in dynamic delivery systems, through the study of a series of models with a highly simplified geometry, exploring the structure of optimal solutions and providing efficient algorithms to solve some vehicle routing and demand management (order acceptance strategies used when the system is overwhelmed by demand) problems.