Journal article
Drone-based hybrid charging for multiple sensors: A distributionally robust optimization approach
Computers & operations research, v 166, 106621
Jun 2024
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The drone-based charging is emerging as a promising way to supply electricity to sensors that keep the Internet of Things working. One-to-one and one-to-many charging strategies can both be adopted. In this background, how to dispatch drones and decide the charging strategy becomes an important problem. In this paper, we first investigate the electricity consumption uncertainty during drone travel, and then develop a distributionally robust hover location and routing optimization model with hybrid charging strategies. After that, we transform the established model into a tractable mixed-integer linear programming model based on dual theory. In order to solve it, we introduce a pre-screening process based on greedy algorithm to select the candidate hover locations. Finally, we conduct extensive numerical experiments and sensitive analysis to verify the efficacy and advantages of the proposed method. We find that the optimized charging strategies and drone dispatching schemes can vary with different sensor distribution patterns. Valuable managerial insights are also provided for drone-based hybrid charging in practice.
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Details
- Title
- Drone-based hybrid charging for multiple sensors: A distributionally robust optimization approach
- Creators
- Xiaoyang Zhou - Xi'an Jiaotong UniversityTingting Guo - Xidian UniversityShouyang Wang - School of Economics and Management, Chinese Academy of Sciences, Beijing 100190, ChinaBenjamin Lev - LeBow College of Business, Drexel University, Philadelphia, PA 19104, USAZhe Zhang - Nanjing University of Science and Technology
- Publication Details
- Computers & operations research, v 166, 106621
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:001217738500001
- Scopus ID
- 2-s2.0-85188745703
- Other Identifier
- 991021864117904721
UN Sustainable Development Goals (SDGs)
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Industrial
- Operations Research & Management Science