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Approximate Covering with Lower and Upper Bounds via LP Rounding

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 نشر من قبل Sayan Bandyapadhyay
 تاريخ النشر 2020
  مجال البحث الهندسة المعلوماتية
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In this paper, we study the lower- and upper-bounded covering (LUC) problem, where we are given a set $P$ of $n$ points, a collection $mathcal{B}$ of balls, and parameters $L$ and $U$. The goal is to find a minimum-sized subset $mathcal{B}subseteq mathcal{B}$ and an assignment of the points in $P$ to $mathcal{B}$, such that each point $pin P$ is assigned to a ball that contains $p$ and for each ball $B_iin mathcal{B}$, at least $L$ and at most $U$ points are assigned to $B_i$. We obtain an LP rounding based constant approximation for LUC by violating the lower and upper bound constraints by small constant factors and expanding the balls by again a small constant factor. Similar results were known before for covering problems with only the upper bound constraint. We also show that with only the lower bound constraint, the above result can be obtained without any lower bound violation. Covering problems have close connections with facility location problems. We note that the known constant-approximation for the corresponding lower- and upper-bounded facility location problem, violates the lower and upper bound constraints by a constant factor.



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