Forecast horizons and dynamic facility location planning
Annals of Operations Research - Special issue on locational decisions
Continuous Reverse Nearest Neighbor Monitoring
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Nearest and reverse nearest neighbor queries for moving objects
The VLDB Journal — The International Journal on Very Large Data Bases
Continuous Reverse k-Nearest-Neighbor Monitoring
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Continuous Reverse Nearest Neighbor Queries on Moving Objects in Road Networks
WAIM '08 Proceedings of the 2008 The Ninth International Conference on Web-Age Information Management
Efficient method for maximizing bichromatic reverse nearest neighbor
Proceedings of the VLDB Endowment
Optimal network location queries
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Optimal location queries in road network databases
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Influence zone: Efficiently processing reverse k nearest neighbors queries
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks
The VLDB Journal — The International Journal on Very Large Data Bases
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
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Given a set S of sites and a set O of weighted objects located on a road network, the optimal network location (ONL) query computes a location on the road network where introducing a new site would maximize the total weight of the objects that are closer to the new site than to any other site. The existing solutions for optimal network location query assume that sites and objects rarely change their location over time, whereas there are numerous new applications with which sites and/or objects frequently change location. Unfortunately, the existing solutions for optimal network location query are not applicable to answer such these so-called dynamic optimal network location queries (DONL), since the result generated by such solutions is most probably invalid by the time computation is complete. In this paper for the first time we formalize the problem of DONL queries as Continuous Maximal Reverse Nearest Neighbor (CMaxRNN) queries on spatial networks, and introduce an approach that allows for efficient and incremental update of MaxRNN query results on spatial networks. With an extensive experimental study we verify and evaluate the efficiency of our proposed approach with both synthetic and real-world datasets.