Journal article
3D Hover Location and Drone Routing Optimization for One-to-Many Continuous Wireless Charging Problem
IEEE transactions on engineering management, v 72, pp 1-18
28 Oct 2024
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The internet of things presents a significant economic value potential, where sensors play a crucial role in its infrastructure. However, the restricted electricity of sensors limits the lifespan of the entire network. The development of modern charging technology has made it possible to realize simultaneous one-to-many charging using drones. To make better use of this charging technology, this paper investigates the problem of charging sensors by drones in three-dimensional (3D) space. Differing from the existing literature, the 3D hovering location of the drone affects the number of sensors being charged simultaneously and consequently the service time of charging. Additionally, we consider the scenario where multiple drones service sensors in the same area, necessitating the assurance of continuous charging services. We propose a mixed integer formulation model to minimize the total cost of completing the recharging task. To solve this problem, an improved genetic algorithm is developed. Extensive experiments are conducted to show the superiority of our proposed method, the effect of one-to-many wireless charging mode, and the sensitivities of the results to the parameters including charging radius and wind scale. This research contributes to further insights into the optimization of wireless charging strategies for sensor networks and other similar problems.
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Details
- Title
- 3D Hover Location and Drone Routing Optimization for One-to-Many Continuous Wireless Charging Problem
- Creators
- Xiaoyang Zhou - Xi'an Jiaotong UniversityJiaao Xu - Xi'an Jiaotong UniversityTingting Guo - Beijing Institute of TechnologyShouyang Wang - Chinese Academy of SciencesBenjamin Lev - Drexel University
- Publication Details
- IEEE transactions on engineering management, v 72, pp 1-18
- Publisher
- IEEE; PISCATAWAY
- Number of pages
- 18
- Grant note
- National Natural Science Foundation of China: 72271194 Key Research and Development Program of Shaanxi Province: 2023GXLH-036
This work was supported in part by the National Natural Science Foundation of China under Grant 72271194 and in part by the Key Research and Development Program of Shaanxi Province under Grant 2023GXLH-036.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:001392784000012
- Scopus ID
- 2-s2.0-85208358771
- Other Identifier
- 991021955315304721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Business
- Engineering, Industrial
- Management