Α decision support system for effective ship weather routing

This study proposes a hybrid decision support system (DSS) for ship weather routing (SWR) under dynamic environmental conditions. Its main contribution is an iterative route-refinement framework that integrates A* pathfinding with the Probabilistic Roadmap Method (PRM), combining efficient global guidance with flexible exploration of safer and smoother alternatives. A* first generates a coarse route that dynamically defines a restricted navigable region, within which PRM searches for improved paths. Successive iterations progressively refine the route while maintaining computational efficiency, enabling near-optimal solutions in less than one minute on a standard PC. Experiments using real-world oceanographic data from the Copernicus Marine Service demonstrate fuel savings of up to 8.7% over baseline shortest-path routing, together with improved route smoothness and reduced exposure to adverse weather conditions. These results demonstrate the effectiveness of hybrid path-planning for real-time SWR and suggest its applicability to other dynamic routing and logistics problems.