An optimization algorithm for operational area allocation in unmanned aerial vehicle systems for search-and-rescue missions
Published: July 5, 2026
Abstract
This study investigates the operational planning process for a multi-drone system operating on a digital map in search-and-rescue missions. Based on a mission area represented in polygonal form, the proposed system performs area partitioning according to the number of deployed drones, generates survey waypoints, and constructs candidate flight trajectories within each subregion. To optimize mission efficiency, three trajectory-planning approaches were comparatively evaluated, including the zigzag algorithm, the nearest neighbor algorithm combined with 2-opt local search, and the ant colony optimization algorithm. The primary evaluation criterion was the total trajectory length generated by each method. Experimental results conducted on a 2.54-hectare survey area under two deployment configurations involving three and four drones demonstrated that the nearest neighbor algorithm integrated with 2-opt local search consistently produced the shortest and most efficient trajectories. The findings confirm the effectiveness of the proposed operational planning framework and highlight its potential for integration into mission-planning subsystems for coordinated multi-drone search-and-rescue operations
Keywords
Dronesflight path planningsearch and rescuedigital mapping
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