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Largest area convex hull of imprecise data based on axis-aligned squares

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Abstract

In recent years, more and more algorithms related to imprecise data have been proposed. Specifically, some algorithms on computing the maximum area convex hull are designed recently when the imprecise data are modeled as non-overlapping axis-aligned squares or as equal size squares. The time complexity of the best known algorithm based on non-overlapping axis-aligned squares is O(n 7). If the squares have equal size and can overlap, the time complexity of the best known algorithm is O(n 5). In this paper, we improve the former from O(n 7) to O(n 5) and improve the latter from O(n 5) to O(n 2). These results are obtained by exploiting the non-trivial geometric properties of the problems.

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Acknowledgements

This research is partially supported by NSF of China under grant 60928006, International Science & Technology Cooperation Program of China (2010DFA92720), Shenzhen Fundamental Research Project (JC201005270342A) and the Opening Fund of Top Key Discipline of Computer Software and Theory in Zhejiang Provincial Colleges at Zhejiang Normal University. We also thank anonymous reviewers for several constructive comments.

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Correspondence to Jun Luo.

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Ju, W., Luo, J., Zhu, B. et al. Largest area convex hull of imprecise data based on axis-aligned squares. J Comb Optim 26, 832–859 (2013). https://doi.org/10.1007/s10878-012-9488-5

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