Ballast Water Inspection Planning with Drones Considering Partial Charging

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.