Abstract
The MaxBRNN problem is to find an optimal region such that setting up a new service site within this region might attract the maximal number of customers by proximity. It has many practical applications such as service location planning and emergency schedule. Typical real-life applications are most in planar space, and the data volume of the problem is huge and thus an efficient solution is highly desired. In this paper, we propose an efficient algorithm, namely, OptRegion, to tackle the MaxBRNN problem in a two-dimensional space. Our methods employ three optimization techniques, i.e., sweep line, pruning strategy (based on upper bound estimation), and influence value computation (of candidate points), to improve the search performance. Extensive experimental evaluation using both real and synthetic datasets confirms that OptRegion outperforms the existing ones significantly under all problem instances.
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Lin, H., Chen, F., Gao, Y., Lu, D. (2013). OptRegion: Finding Optimal Region for Bichromatic Reverse Nearest Neighbors. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds) Database Systems for Advanced Applications. DASFAA 2013. Lecture Notes in Computer Science, vol 7825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37487-6_13
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DOI: https://doi.org/10.1007/978-3-642-37487-6_13
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