Capacitated k-Centers

During my half-year research visit at the University of Maryland, I had a chance to work with MohammadTaghi Hajiaghayi and Samir Khuller, which resulted in a paper accepted to FOCS 2012: LP Rounding for k-Centers with Non-uniform Hard Capacities (to appear in arXiv soon).

In the k-center problem, we are given an integer k and a metric dist defined on a given set of points V. The goal is to open exactly k centers, that is facilities that are to serve clients located in all the points of V, in such a way that the maximum distance between any point of V and its closest center is minimized. Simple 2-approximation algorithms are known for this problem since 80's, and by a reduction from dominating set no (2-eps)-approximation algorithm exists unless P=NP.

In the capacitated version, each point v of V is assigned its capacity L(v) and in this setting no center can serve more clients than its capacity. The special case when all the capacities are equal was studied in 90's, when Bar-Ilan, Kortsarz and Peleg gave a 10-approximation algorithm, which was later improved to 6-approximation by Khuller and Sussmann. In this paper we present a constant factor approximation algorithm for the general capacities case.

By the standard tresholding technique, one can assume that the metric dist is a shortest path metric in a given undirected unweighted graph G=(V,E). This can be achieved by guessing the value of OPT (there are only n2 possibilities) and putting to the edge set all pairs at distance at most OPT. Unfortunately, even after this reduction the standard LP relaxation has unbounded integrality gap, which can be seen at the following example, where k=3 and the capacity function is uniform L(v)=4.

However, what we found surprising, when the given graph G is connected we were able to prove a constant upper bound on the integrality gap of the LP. Since one can solve the problem for each connected component of the graph independently and combine results using standard dynamic programming, a rounding algorithm for connected graphs is enough to obtain a constant factor approximation algorithm.

Let y-value of a vertex be the fraction of a center opened in it by the fractional LP solution we are working with. Since we have a sharp bound on the number of centers opened, we can not independently round y-values of vertices, because we have to preserve the sum of y-values. For this reason we use what we call chain shifting operation, where in order to move y-value between two distant vertices a and b we use intermediate fully opened (with y-value equal to one) centers as illustrated below.


Observe, that in the above figure in order to move clients between the centers we need an assumption, that all the internal vertices of the path have capacities at least L(a). This is the main obstacle in our rounding process, which clearly would not appear in the uniform capacities case. This hurdle makes our algorithm technical, as we round the fractional LP solution in several steps, where in each step we get more structure on the fractionally opened centers, at the cost of increasing distances between centers and clients those are serving.

Finally we would like to mention some open problems. The approximation ratio we obtain is in the order of hundreds (however we do not calculate it explicitly), so the natural open problem is to give an algorithm with a reasonable approximation ratio. Moreover, we have shown that the integrality gap of the standard LP formulation for connected graphs in the uniform capacities case is either 5 or 6, which we think might be an evidence, that it should be possible to narrow the gap between the known lower bound (2-eps) and upper bound 6 in the uniform capacities case.

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