A Risk-Driven Maritime Patrol Route Optimization Framework for IUU Fishing Surveillance Using Multi-Source AIS and SAR Data Fusion

Illegal, unreported, and unregulated (IUU) fishing threatens marine ecosystems in the Western Pacific. Traditional patrol strategies suffer from low efficiency due to insufficient utilization of multi-source surveillance data. This study proposes a maritime patrol framework integrating AIS fishing effort, Sentinel-1 SAR dark vessel detections, and vessel encounter records. An Adaptive Priority-Boosted Ant Colony Optimization (APB-ACO) algorithm with two-phase deadline-aware construction ensures high-priority coverage within 72 hours while minimizing total distance. Experiments on real satellite datasets demonstrate that APB-ACO achieves 7% shorter routes with 46× lower variance than conventional methods, with 100% high-priority task coverage. The framework provides an effective decision-support tool for maritime law enforcement. This framework can serve as a practical decision-support tool for maritime law enforcement and marine resource management.