Navigating through conflict zones poses significant risks and challenges. Using Python, this project applies the pathfinding technique Dijkstra's algorithm to identify the quickest route between "drop off" and "target" locations in a real-world conflict zone in Yemen, avoiding "enemy camps" and conflict-prone areas. Conflict data was acquired from the Cities and Armed Conflict Events (CACE) dataset (2020-2023).
My analysis is simplified and assumes movement is unaffected by terrain. In practice, movement ease depends on topography (e.g., elevation and water bodies) and the presence of human-made structures such as roads, bridges, and urban areas.
Figure 1 Optimized route through conflict zones, avoiding enemy bases. The heatmap indicates conflict intensity, and the black dotted line shows the shortest safe path.