Artificial Intelligence and Logistics AILog 2012 Workshop Proceedings

We present a new algorithm to find optimal routes in a multi-modal public transportation network. This work is an extension of recent work on finding multi-criteria optimal paths in multi-modal public transportation networks [8] using the ideas of TRANSIT algorithm [4]. As a preprocessing step, we identify hub stations, a relatively small subset of all stations and then precompute optimal paths only between those hubs. Given a query between any two locations we show how to extract the optimal path in an efficient way using those hubs. In addition we present an improvement of our algorithm using service patterns. This allows us to significantly reduce both memory requirements and preprocessing time of previously reported algorithm by order of magnitude. Finally, we present results of our experiments on the Sydney metropolitan and the New South Wales state public transport networks.