GPS Routing of Shortest Path through Kernel Algorithm

Global Positioning System (GPS) navigation relies on finding optimal routes between locations. This paper presents a new algorithm based on kernel methods to efficiently solve the GPS routing shortest path problem. The algorithm models complex relationships between locations using kernel functions to prune the search space and identify ideal paths. We prove the algorithm guarantees globally optimal routes and runs in quadratic time, outperforming traditional methods. Implementing the algorithm on real-world road networks demonstrates superior performance, finding shortest paths orders of magnitude faster compared to benchmarks like Dijkstra's algorithm. Additional optimizations further improve scalability and efficiency. Case studies showcase applications in traffic navigation, logistics, and emergency response. The kernel algorithm's novel formulation, optimality guarantees, and empirical results on large-scale GPS routing problems highlight its potential as an enabling technique for next-generation navigation systems.