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Computing the shortest pathA search meets graph theory
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Source Symposium on Discrete Algorithms archive
Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms table of contents
Vancouver, British Columbia
SESSION: Session 3A table of contents
Pages: 156 - 165  
Year of Publication: 2005
ISBN:0-89871-585-7
Authors
Andrew V. Goldberg  Microsoft Research, Mountain View, CA
Chris Harrelson  UC Berkeley
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
: SIAM Activity Group on Discrete Mathematics
Publisher
Society for Industrial and Applied Mathematics  Philadelphia, PA, USA
Bibliometrics
Downloads (6 Weeks): 39,   Downloads (12 Months): 279,   Citation Count: 21
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ABSTRACT

We propose shortest path algorithms that use A* search in combination with a new graph-theoretic lower-bounding technique based on landmarks and the triangle inequality. Our algorithms compute optimal shortest paths and work on any directed graph. We give experimental results showing that the most efficient of our new algorithms outperforms previous algorithms, in particular A* search with Euclidean bounds, by a wide margin on road networks and on some synthetic problem families.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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A. Goldberg and C. Harrelson. Computing the Shortest Path: A* Search Meets Graph Theory. Technical Report MSR-TR-2004-24, Microsoft Research, 2004.
 
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CITED BY  21
Collaborative Colleagues:
Andrew V. Goldberg: colleagues
Chris Harrelson: colleagues