Efficient Algorithms for Earliest and Fastest Paths in Public Transport Networks

TL;DR

This paper introduces linear-time algorithms for the earliest arrival time and fastest path problems in public transport networks, significantly improving computational efficiency and aiding urban transport management.

Contribution

The study presents novel linear-time algorithms for extsc{eat} and extsc{fpd} problems, outperforming existing methods in speed.

Findings

34-fold speedup for fastest path problem

183-fold speedup for earliest arrival time problem

Substantial efficiency improvements demonstrated

Abstract

Public transport administrators rely on efficient algorithms for various problems that arise in public transport networks. In particular, our study focused on designing linear-time algorithms for two fundamental path problems: the earliest arrival time (\textsc{eat}) and the fastest path duration (\textsc{fpd}) on public transportation data. We conduct a comparative analysis with state-of-the-art algorithms. The results are quite promising, indicating substantial efficiency improvements. Specifically, the fastest path problem shows a remarkable 34-fold speedup, while the earliest arrival time problem exhibits an even more impressive 183-fold speedup. These findings highlight the effectiveness of our algorithms to solve \textsc{eat} and \textsc{fpd} problems in public transport, and eventually help public administrators to enrich the urban transport experience.