The Heterogeneous Capacitated $k$-Center Problem

November 22, 2016 Β· Declared Dead Β· πŸ› Conference on Integer Programming and Combinatorial Optimization

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Authors Deeparnab Chakrabarty, Ravishankar Krishnaswamy, Amit Kumar arXiv ID 1611.07414 Category cs.DS: Data Structures & Algorithms Citations 7 Venue Conference on Integer Programming and Combinatorial Optimization Last Checked 4 months ago
Abstract
In this paper we initiate the study of the heterogeneous capacitated $k$-center problem: given a metric space $X = (F \cup C, d)$, and a collection of capacities. The goal is to open each capacity at a unique facility location in $F$, and also to assign clients to facilities so that the number of clients assigned to any facility is at most the capacity installed; the objective is then to minimize the maximum distance between a client and its assigned facility. If all the capacities $c_i$'s are identical, the problem becomes the well-studied uniform capacitated $k$-center problem for which constant-factor approximations are known. The additional choice of determining which capacity should be installed in which location makes our problem considerably different from this problem, as well the non-uniform generalizations studied thus far in literature. In fact, one of our contributions is in relating the heterogeneous problem to special-cases of the classical Santa Claus problem. Using this connection, and by designing new algorithms for these special cases, we get the following results: (a)A quasi-polynomial time $O(\log n/Ξ΅)$-approximation where every capacity is violated by $1+\varepsilon$, (b) A polynomial time $O(1)$-approximation where every capacity is violated by an $O(\log n)$ factor. We get improved results for the {\em soft-capacities} version where we can place multiple facilities in the same location.
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