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The multi-rule partial sequenced route query
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Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents
Irvine, California
SESSION: Route finding and road networks table of contents
Article No. 10  
Year of Publication: 2008
ISBN:978-1-60558-323-5
Authors
Haiquan Chen  Auburn University, Auburn, AL
Wei-Shinn Ku  Auburn University, Auburn, AL
Min-Te Sun  National Central University, Taoyuan, Taiwan
Roger Zimmermann  National University of Singapore, Singapore
Sponsors
: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft
Publisher
ACM  New York, NY, USA
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ABSTRACT

Trip planning search (TPS) represents an important class of queries in Geographic Information Systems (GIS). In many real-world applications, TPS requests are issued with a number of constraints. Unfortunately, most of these constrained TPS cannot be directly answered by any of the existing algorithms. By formulating each restriction into rules, we propose a novel form of route query, namely the multi-rule partial sequenced route (MRPSR) query. Our work provides a unified framework that also subsumes the well-known trip planning query (TPQ) and the optimal sequenced route (OSR) query. In this paper, we first prove that MRPSR is NP-hard and then present three heuristic algorithms to search for near-optimal solutions for the MRPSR query. Our extensive simulations show that all of the proposed algorithms can answer the MRPSR query effectively and efficiently. Using both real and synthetic datasets, we investigate the performance of our algorithms with the metrics of the route distance and the response time in terms of the percentage of the constrained points of interest (POI) categories. Compared to the LORD-based brute-force solution, the response times of our algorithms are remarkably reduced while the resulting route length is only slightly longer than the shortest route.


REFERENCES

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Collaborative Colleagues:
Haiquan Chen: colleagues
Wei-Shinn Ku: colleagues
Min-Te Sun: colleagues
Roger Zimmermann: colleagues