A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Computing the shortest path: A search meets graph theory
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Dynamic Travel Time Maps - Enabling Efficient Navigation
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Partitioning graphs to speedup Dijkstra's algorithm
Journal of Experimental Algorithmics (JEA)
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
A new perspective on efficient and dependable vehicle routing
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Engineering fast route planning algorithms
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
Contraction hierarchies: faster and simpler hierarchical routing in road networks
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
Goal directed shortest path queries using precomputed cluster distances
WEA'06 Proceedings of the 5th international conference on Experimental Algorithms
Highway hierarchies hasten exact shortest path queries
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Crowdsourcing computing resources for shortest-path computation
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Towards a Flexible and Scalable Fleet Management Service
Proceedings of the Sixth ACM SIGSPATIAL International Workshop on Computational Transportation Science
Optimizing Landmark-Based Routing and Preprocessing
Proceedings of the Sixth ACM SIGSPATIAL International Workshop on Computational Transportation Science
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While many efficient proposals exist for solving the single-pair shortest-path problem, a solution that sees the algorithmic solution in combination with efficient data management has received considerably smaller attention. This work proposes a data management approach for efficient shortest path computation that exploits road network hierarchies and allow us to minimize the portion of the network that is kept in main memory. The proposed approach is insensitive to network changes as it does not rely on any pre-computation, but only on given road network properties. In that we specifically target large road networks that exhibit a high degree of change (e.g., OpenStreetMap). Extensive experimental evaluation shows that the presented solution is both efficient and scalable and provides competitive shortest-path computation performance without requiring a preprocessing stage for the road network graph.