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Investigating the impact of area characteristics on delivery model decisions


Term:

Spring-Summer

Department:

CTL: Center for Transportation & Logistics

Faculty Supervisor:

Matthias Winkenbach

Faculty email:

mwinkenb@mit.edu

Apply by:

02/15/2020

Contact:

Jonas Lehmann: lehmannj@mit.edu

Project Description

The demand for package deliveries is growing steadily due to the rise in e-commerce and on-demand consumerism. Parcel delivery companies, for a long time relying on their traditional truck-only delivery systems, are looking for new and advanced multi-echelon and multi-modal delivery models, such as truck and drone, bike couriers or trailer-based 2-echelon models. While the cost and network design of the companies play into the decision making process of which delivery model is the most suitable, we aim to understand the implicit impact of area characteristics on the delivery model decisions. In that context we will perform a large-scale data analysis with area characteristics from dozens of cities in the US and worldwide on real-world customer data. For this project, we look for a UROP setting up the data pipeline for the area characteristics from public data sources, such as urban density, road network and settlement structures. Further contributions through literature review or data analysis is possible. This position is part of an industry project with one of the largest parcel delivery companies in the world and offers first-hand insights on actual business decision making and cutting edge research. Further, the position offers a steep learning curve both in domain knowledge of the vastly expanding last-mile logistics field but also methodological capabilities like vehicle routing optimization and data analytics.

Pre-requisites

Students with interest in transportation research and familiarity with Python and SQL are welcome to apply