We introduce and study the {\em donation center location} problem, which has an additional application in network testing and may also be of independent interest as a general graph-theoreticproblem.Given a set of agents and a set of centers, where agents have preferences over centers and centers have capacities, the goal is to open a subset of centers and to assign a maximum-sized subset of agents to their most-preferred open centers, while respecting the capacity constraints. We prove that in general, the problem is hard to approximate within $n^{1/2-\epsilon}$ for any $\epsilon>0$. In view of this, we investigate two special cases. In one, every agent has a bounded number of centers on her preference list, and in the other, all preferences are induced by a line-metric. We present constant-factor approximation algorithms for the former and exact polynomial-time algorithms for the latter. Of particular interest among our techniques are an analysis of the greedy algorithm for a variant of the maximum coverage problem called\emph{frugal coverage}, the use of maximum matching subroutine with subsequent modification, analyzed using a counting argument, and a reduction to the independent set problem on \emph{terminal intersection graphs}, which we show to be a subclass of trapezoid graphs.
@InProceedings{huang_et_al:LIPIcs.FSTTCS.2009.2321, author = {Huang, Chien-Chung and Svitkina, Zoya}, title = {{Donation Center Location Problem}}, booktitle = {IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science}, pages = {227--238}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-939897-13-2}, ISSN = {1868-8969}, year = {2009}, volume = {4}, editor = {Kannan, Ravi and Narayan Kumar, K.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2009.2321}, URN = {urn:nbn:de:0030-drops-23212}, doi = {10.4230/LIPIcs.FSTTCS.2009.2321}, annote = {Keywords: Approximation Algorithms, Facility Location, Matching with Preferences} }
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