A range-restricted recharging station coverage model for drone delivery service planning |
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Affiliation: | 1. Department of Geology and Geography, West Virginia University, United States;2. School of Geographical Sciences and Urban Planning, Arizona State University, United States;3. Department of Geography, University of California at Santa Barbara, United States;1. ICTEAM, Université catholique de Louvain, Belgium;2. SoICT, Hanoi University of Science and Technology, Viet Nam;3. University of Engineering and Technology, Vietnam National University, Hanoi (VNU), Viet Nam;1. School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA;2. Department of Industrial & Management Systems Engineering, Dong-A University, Busan, Republic of Korea;3. Defense Modeling and Simulation Division, Korea Institute for Defence Analyses, Seoul, Republic of Korea |
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Abstract: | Unmanned Aerial Vehicles (UAVs) are attracting significant interest for delivery service of small packages in urban areas. The limited flight range of electric drones powered by batteries or fuel cells requires refueling or recharging stations for extending coverage to a wider area. To develop such service, optimization methods are needed for designing a network of station locations and delivery routes. Unlike ground-transportation modes, however, UAVs do not follow a fixed network but rather can fly directly through continuous space. But, paths must avoid barriers and other obstacles. In this paper, we propose a new location model to support spatially configuring a system of recharging stations for commercial drone delivery service, drawing on literature from planar-space routing, range-restricted flow-refueling location, and maximal coverage location. We present a mixed-integer programming formulation and an efficient heuristic algorithm, along with results for a large case study of Phoenix, AZ to demonstrate the effectiveness and efficiency of the model. |
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Keywords: | Unmanned aerial vehicles Spatial optimization Euclidean Shortest Path GIS Location modeling |
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