The Optimized path for the public transportation of Incheon in South Korea
This addresses route optimization for public transportation systems in a specific city, representing an incremental improvement.
The paper tackles the problem of finding optimal bus routes in Incheon, South Korea, based on passenger demand, and shows that a modified A* algorithm outperforms basic algorithms like Genetic and Dijkstra in finding the shortest path in real-time for large datasets.
Path-finding is one of the most popular subjects in the field of computer science. Pathfinding strategies determine a path from a given coordinate to another. The focus of this paper is on finding the optimal path for the bus transportation system based on passenger demand. This study is based on bus stations in Incheon, South Korea, and we show that our modified A* algorithm performs better than other basic pathfinding algorithms such as the Genetic and Dijkstra. Our proposed approach can find the shortest path in real-time even for large amounts of data(points).