An A* Algorithm Framework for the Point-to-Point Time-Dependent Shortest Path Problem

  • Tatsuya Ohshima
  • Pipaporn Eumthurapojn
  • Liang Zhao
  • Hiroshi Nagamochi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7033)


Given a directed graph, a nonnegative transit-time function c e (t) for each edge e (where t denotes departure time at the tail of e), a source vertex s, a destination vertex d and a departure time t 0, the point-to-point time-dependent shortest path problem (TDSPP) asks to find an s,d-path that leaves s at time t 0 and minimizes the arrival time at d. This formulation generalizes the classical shortest path problem in which c e are all constants.

This paper presents a novel generalized A* algorithm framework by introducing time-dependent estimator functions. This framework generalizes previous proposals that work with static estimator functions. We provide sufficient conditions on the time-dependent estimator functions for the correctness. As an application, we design a practical algorithm which generalizes the ALT algorithm for the classical problem (Goldberg and Harrelson, SODA05). Finally experimental results on several road networks are shown.


Road Network Estimator Function Short Path Problem Algorithm Framework Fast Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tatsuya Ohshima
    • 1
  • Pipaporn Eumthurapojn
    • 2
  • Liang Zhao
    • 2
  • Hiroshi Nagamochi
    • 2
  1. 1.JFE Steel CorporationKurashikiJapan
  2. 2.Graduate School of InformaticsKyoto UniversityJapan

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