Document Type : Research Paper
Authors
1 School of Business Jiangnan University Jiangsu Wuxi China
2 School of Business, Jiangnan University Jiangsu Wuxi China
Abstract
Unmanned aerial vehicle (UAV) safety inspection is a developing technology that offers the benefits of high efficiency, low cost, and freedom from dangerous areas and unique situations. An urgent fundamental issue in the deployment of UAV in factories is how to successfully strike a balance between the effectiveness and cost of UAV safety inspection. In view of this, we build a route planning model for UAV inspection. And then, by using the path planning of UAV safety inspection as the research object, based on the two important evaluation indicators of cost and efficiency, we exploit fuzzy time window and adaptive genetic algorithms to design the solution algorithm. Finally, a case verifies the applicability and logic of the proposed model. The results show that the proposed path optimization model with fuzzy time window can reasonably pass all inspection points under balanced conditions, and the hybrid genetic algorithm has good optimization ability.
Keywords
Main Subjects
Electronics, 9(2) (2020), 260. https://doi.org/10.3390/electronics9020260
Computing and Applications, 34(7) (2022), 5649-5664. https://doi.org/10.1007/s00521-021-06702-3
vehicle, Advanced Engineering Informatics, 55 (2023), 101829. https://doi.org/10.1016/j.aei.2022.101829
System Simulation, 34(6) (2022), 1275-1285. https://doi.org/10.16182/j.issn1004731x.joss.21-1121
dynamic environment, Ad Hoc Networks, 140 (2023), 103068. https://doi.org/10.1016/j.adhoc.2022.103068
forest environment, Frontiers in Neurorobotics, 16 (2022), 1105177. https://doi.org/10.3389/fnbot.2022.
1105177
Advances in Distributed Computing and Artificial Intelligence Journal, 11(2) (2022), 179-189. https://doi.org/
10.14201/adcaij.27533
and algorithm, Annals of Operations Research, (2023), 1-29. https://doi.org/10.1007/s10479-022-05102-7
with moving obstacles based on an improved pigeon-inspired optimization algorithm, Applied Intelligence, 50 (2020),
2800-2817. https://doi.org/10.1007/s10489-020-01650-2
International Journal of Applied Earth Observation and Geoinformation, 111 (2022), 102857. https://doi.org/
10.1016/j.jag.2022.102857
multiple time windows, Transportation Science, 54(2) (2020), 400-416. https://doi.org/10.1287/trsc.2019.
0912
and perspectives, Frontiers in Energy Research, 9 (2021), 713634. https://doi.org/10.3389/fenrg.2021.713634
Sustainability, 14(20) (2022), 13421. https://doi.org/10.3390/su142013421
Things Journal, 7(9) (2020), 8967-8978. https://doi.org/10.1109/JIOT.2020.2999083
vertical and horizontal kernels, Sensors, 20(20) (2020), 5759. https://doi.org/10.3390/s20205759
applications, IEEE Transactions on Nanobioscience, 14(8) (2015), 811-817. https://doi.org/10.1109/TNB.2015.
2478481
[17] H. ¨ Oztop, D. Kizilay, Z. A. C¸ il, Mathematical models for the periodic vehicle routing problem with time windows
and time spread constraints, An International Journal of Optimization and Control: Theories and Applications,
11(1) (2021), 10-23. https://doi.org/10.11121/ijocta.01.2021.00899
Applied Soft Computing, 107 (2021), 107376. https://doi.org/10.1016/j.asoc.2021.107376
(2021), 144. https://doi.org/10.3390/drones5040144
Technology, 45(9) (2021), 3636-3648. https://doi.org/10.13335/j.1000-3673.pst.2020.1178
https://doi.org/10.3390/drones6050134
https://doi.org/10.3390/f13111952
Computer Communications, 162 (2020), 196-203. https://doi.org/10.1016/j.comcom.2020.04.050
138 (2023), 103018. https://doi.org/10.1016/j.adhoc.2022.103018
scenarios, Knowledge-Based Systems, 204 (2020), 106209. https://doi.org/10.1016/j.knosys.2020.106209
Research, 93 (2019), 410-416. https://doi.org/10.2112/SI93-054.1
(2021), 98. https://doi.org/10.3390/drones5030098
multi-type vehicle routing problem with time windows, Computers and Industrial Engineering, 171 (2022), 108435.
https://doi.org/10.1016/j.cie.2022.108435
reinforcement learning for path planning of unmanned air vehicles, Knowledge-Based Systems, 250 (2022), 109075.
https://doi.org/10.1016/j.knosys.2022.109075
path planning, Aerospace Science and Technology, 118(1) (2021), 107004. https://doi.org/10.1016/j.ast.2021.
107004
UAV in an unknown environment, ISPRS International Journal of Geo-Information, 10(10) (2021), 631. https:
//doi.org/10.3390/ijgi10100631