Vessel-risk-aware: a decision support model for vessel routing based on multicriteria decision analysis and an advanced Dijkstra algorithm

Maritime weather routing research has largely prioritized minimizing operating costs, fuel consumption, and estimated time of arrival (ETA). However, existing models often neglect accident avoidance and environmental risks. Fishing vessels particularly face many challenges from dynamic coastal hazards, frequent operational stops, and diverse safety thresholds. This study proposes a multicriteria spatial decision support system (SDSS) that integrates an enhanced Dijkstra algorithm with Weighted Sum Model (WSM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to address these gaps. The framework advances maritime navigation through three major contributions. First, it incorporates eight-directional pathfinding into the Dijkstra algorithm to better account for coastal navigation constraints. Second, it integrates dynamic vulnerability indices derived from bathymetry, wave conditions, and vessel speed, calibrated against historical accident data to reflect real-world risk. Third, it provides an interactive interface that enables stakeholders to assign relative importance to safety, efficiency, and environmental criteria, thereby fostering transparent and collaborative decision-making. Together, these innovations generate optimized routes that balance multiple objectives under varying oceanic conditions such as wind, waves, and currents. By bridging theoretical routing models with the practical demands of fisheries management, this framework offers a scalable tool for safer maritime navigation in weather-dependent contexts.