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We consider the $k$-center problem in which the centers are constrained to lie on two lines. Given a set of $n$ weighted points in the plane, we want to locate up to $k$ centers on two parallel lines. We present an $O(nlog^2 n)$ time algorithm, which minimizes the weighted distance from any point to a center. We then consider the unweighted case, where the centers are constrained to be on two perpendicular lines. Our algorithms run in $O(nlog^2 n)$ time also in this case.
We study the $k$-center problem in a kinetic setting: given a set of continuously moving points $P$ in the plane, determine a set of $k$ (moving) disks that cover $P$ at every time step, such that the disks are as small as possible at any point in ti
The Euclidean $k$-center problem is a classical problem that has been extensively studied in computer science. Given a set $mathcal{G}$ of $n$ points in Euclidean space, the problem is to determine a set $mathcal{C}$ of $k$ centers (not necessarily p
We present algorithms for length-constrained maximum sum segment and maximum density segment problems, in particular, and the problem of finding length-constrained heaviest segments, in general, for a sequence of real numbers. Given a sequence of n r
For any constants $dge 1$, $epsilon >0$, $t>1$, and any $n$-point set $Psubsetmathbb{R}^d$, we show that there is a geometric graph $G=(P,E)$ having $O(nlog^2 nloglog n)$ edges with the following property: For any $Fsubseteq P$, there exists $F^+sups
Given a set $P$ of $n$ points and a set $S$ of $m$ weighted disks in the plane, the disk coverage problem asks for a subset of disks of minimum total weight that cover all points of $P$. The problem is NP-hard. In this paper, we consider a line-const