An Effective Approach for Mass Transit Routing and Optimization

The need for efficient transport management based applications has witnessed a tremendous growth due to the explosive burst in population and the corresponding demand for transport services. In this paper we propose a novel Mass Transit Routing 406 Daning Chen et al. and Optimization Tool (MTRO), which uses Data Mining (DM) techniques to extract information from the commuter database and assist the transport authorities in optimizing routes. Additionally, the application mines the optimal route for a given destination. Association Rule mining technique identifies the frequently used routes. The technique of Data Classification is employed to categorize the paths based on cost and time and suggest the optimal path to a destination. The proposed algorithms give better performance over traditional Frequent Pattern (FP) Growth based approaches with significant reduction in run time and memory usage.