A Shortest Path Searching Method with Area Limitation Heuristics

  • Feng Lu
  • Poh-Chin Lai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3991)


While heuristics based on geometric constructs of the networks would appear to improve performance of Dijkstra’s algorithm, the fallacy of depreciated accuracy has been an obstacle to the wider application of heuristics in the search for shortest paths. The authors presented a shortest path algorithm that employs limited area heuristics guided by spatial arrangement of networks. The algorithm was shown to outperform other theoretically optimal solutions to the shortest path problem and with only little accuracy lost. More importantly, the confidence and accuracy levels were both controllable and predictable.


Short Path Destination Node Short Path Problem Geographic Information System Short Path Algorithm 
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.


  1. Miller, H.J., Shaw, S.L.: Geographic Information Systems for Transportation: Principles and Applications. Oxford University Press, New York (2001)Google Scholar
  2. Zhao, Y.L.: Vehicle Location and Navigation Systems. Artech House Publishers, Boston (1997)MATHGoogle Scholar
  3. Fisher, P.F.: A primer of geographic search using artificial intelligence. Computers and Geosciences 16, 753–776 (1990)CrossRefGoogle Scholar
  4. Car, A., Frank, A.: General principles of hierarchical spatial reasoning-the case of wayfinding. In: Proceedings of the 6th International Symposium on Spatial Data Handling, pp. 646–664 (1994)Google Scholar
  5. Holzer, M., Schulz, F., Willhalm, T.: Combining speed-up techniques for shortest-path computations. In: Ribeiro, C.C., Martins, S.L. (eds.) WEA 2004. LNCS, vol. 3059, pp. 269–284. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. Lu, F., Guan, Y.: An optimum vehicular path solution with multi-heuristics. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3039, pp. 964–971. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Feng Lu
    • 1
  • Poh-Chin Lai
    • 2
  1. 1.State Key Laboratory of Resources and Environmental Information System, The Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingP.R. China
  2. 2.Department of GeographyThe University of Hong KongHong Kong SARP.R. China

Personalised recommendations