.png){kind=icon}
.png){kind=icon}
Return
Ballast Water Inspection Planning with Drones Considering Partial Charging
.png){kind=icon}
OA
AI
X
H
Z
DOI：10.3390/drones10080613.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In maritime safety regulation, conventional ballast water inspection faces critical time-window violations due to manual sampling delays across dispersed inspection points. While drone-based inspection significantly enhances multi-point accessibility and timeliness, its operational viability is severely constrained by limited battery endurance during multi-vessel missions. To address this challenge, we propose a novel partial charging strategy enabling adaptive energy replenishment. This strategy is formalized in a model incorporating dual energy consumption (propulsion and hovering) and spatiotemporal constraints for sampling operations. An adaptive metaheuristic algorithm combining dynamic programming with large neighborhood search is developed for efficient resolution. Computational experiments demonstrate that partial charging strategy reduces drone energy consumption by 25% compared to the 70%-threshold charging strategy. This study provides maritime authorities with a quantifiable configuration decision tool to optimize drone fleets and flight parameters, balancing regulatory compliance with operational costs.
Keywords:
ballast water inspection
drone routing
partial charging strategy
adaptive metaheuristic algorithm
dynamic programming
multi-trip routing
Journal
D
IF:
4.8
Papers:
3.7K
Citations:
8.3K
Organization
Cited Papers