This project focuses on transportation planning for emergency response, from both a behavioral and a modeling perspective. One key element missing from our understanding of humanitarian supply chains is the role of people, whose ability to improvise and to learn from experience may provide some advantages in the humanitarian context. On the other hand, mathematical models can better handle complex information and search large decision spaces. This project seeks to develop better decision-making approaches by understanding and building upon the strengths of people and models.
We focus on the problem of planning aid deliveries after an emergency. The Logistics Cluster must decide how to use its fleet of trucks and helicopters to deliver aid cargo to affected communities, considering efficiency and prioritization of needed cargo. A variety of methods are employed, including ethnographic observations, a stated preference survey, and modeling approaches, in order to determine how humans and models can interact to create better delivery plans. In addition to theoretical contributions, we aim to develop practical tools for transportation planning, in cooperation with humanitarian organizations.