Advancing Dynamic Relief Response: Integration of New Data Streams and Routing Models

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The goals of this research project are to (1) assess how new data streams available during a crisis can improve logistical decisions, and (2) facilitate data stream integration into humanitarian logistics operations, such as search-and-rescue (SAR) and relief distribution efforts. Since the devastating January 2010 Haitian earthquake, there has been an increasing use and a deeper understanding of the role of new technologies in disaster relief, as well as the challenges of integrating these technologies into response activities. The deliverables of this project will be a comprehensive data source taxonomy focused on humanitarian logistics and a formal description of the necessary processes to prepare real-time datasets for use in humanitarian emergencies. Furthermore, this work will identify needed advances in dynamic routing models to accommodate these new data streams and the complex set of decisions in the field. Field-based activities will bring together undergraduate/graduate students, faculty and practitioners.Ultimately, this project will provide a framework for researchers in the field to further this line of work. The project also identifies a new class of routing models that combine orienteering and path planning problems needed to address the challenges of these unique problem settings. Integration of emerging data streams into humanitarian logistics, such as SAR operations, has potential to save lives and minimize suffering of people affected by natural disaster and other crises. The likelihood of success in model creation and implementation in practice will increase with a series of ongoing conversations between practitioners, inter-disciplinary research teams, humanitarian organizations and the broader crisis mapping community. This research will also impact undergraduate and graduate students by exposing them to new applications of their operations research knowledge.