{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/155367"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/155367","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Strategic Planning and Deployment of Aerial Assets","abstract":"The rapid deployment of fleets of small, uncrewed aircraft (drones) for tasks like package delivery or search-and-rescue in the immediate aftermath of a natural disaster are some of the most vital and common applications of advanced air mobility. Recognizing that successful drone missions depend on pre-established, well-positioned bases and efficient task allocation, this work presents a generalizable model for base positioning and routing in diverse applications. The proposed model prioritizes choosing bases that both maximize operational coverage and enable rapid responses to high-demand areas. Additionally, the framework integrates a vehicle routing component to optimize drone flight paths for efficient task completion in the tactical portion of drone-based operations; this component is the primary focus of this work. In addition to the theoretical formulation, the models are validated through case studies examining post-flooding search-and-rescue in the Iwate prefecture of Japan and package deliveries in the Austin, TX metropolitan area.","abstract_html":"The rapid deployment of fleets of small, uncrewed aircraft (drones) for tasks like package delivery or search-and-rescue in the immediate aftermath of a natural disaster are some of the most vital and common applications of advanced air mobility. Recognizing that successful drone missions depend on pre-established, well-positioned bases and efficient task allocation, this work presents a generalizable model for base positioning and routing in diverse applications. The proposed model prioritizes choosing bases that both maximize operational coverage and enable rapid responses to high-demand areas. Additionally, the framework integrates a vehicle routing component to optimize drone flight paths for efficient task completion in the tactical portion of drone-based operations; this component is the primary focus of this work. In addition to the theoretical formulation, the models are validated through case studies examining post-flooding search-and-rescue in the Iwate prefecture of Japan and package deliveries in the Austin, TX metropolitan area.","abstract_has_math":false,"creators":["Saravanan, Akila"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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Recognizing that successful drone missions depend on pre-established, well-positioned bases and efficient task allocation, this work presents a generalizable model for base positioning and routing in diverse applications. The proposed model prioritizes choosing bases that both maximize operational coverage and enable rapid responses to high-demand areas. Additionally, the framework integrates a vehicle routing component to optimize drone flight paths for efficient task completion in the tactical portion of drone-based operations; this component is the primary focus of this work. 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Additionally, the framework integrates a vehicle routing component to optimize drone flight paths for efficient task completion in the tactical portion of drone-based operations; this component is the primary focus of this work. 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