The Parameterized Hardness of the k-Center Problem in Transportation Networks
In this paper we study the hardness of the k-Center problem on inputs that model transportation networks. For the problem, an edge-weighted graph G=(V,E) and an integer k are given and a center set C subseteq V needs to be chosen such that |C|<= k. The aim is to minimize the maximum distance of any vertex in the graph to the closest center. This problem arises in many applications of logistics, and thus it is natural to consider inputs that model transportation networks. Such inputs are often assumed to be planar graphs, low doubling metrics, or bounded highway dimension graphs. For each of these models, parameterized approximation algorithms have been shown to exist. We complement these results by proving that the k-Center problem is W[1]-hard on planar graphs of constant doubling dimension, where the parameter is the combination of the number of centers k, the highway dimension h, and even the treewidth t. Moreover, under the Exponential Time Hypothesis there is no f(k,t,h)* n^{o(t+sqrt{k+h})} time algorithm for any computable function f. Thus it is unlikely that the optimum solution to k-Center can be found efficiently, even when assuming that the input graph abides to all of the above models for transportation networks at once!
Additionally we give a simple parameterized (1+{epsilon})-approximation algorithm for inputs of doubling dimension d with runtime (k^k/{epsilon}^{O(kd)})* n^{O(1)}. This generalizes a previous result, which considered inputs in D-dimensional L_q metrics.
k-center
parameterized complexity
planar graphs
doubling dimension
highway dimension
treewidth
Theory of computation~Fixed parameter tractability
Theory of computation~Facility location and clustering
Theory of computation~Problems, reductions and completeness
19:1-19:13
Regular Paper
https://arxiv.org/abs/1802.08563
Andreas Emil
Feldmann
Andreas Emil Feldmann
Department of Applied Mathematics, Charles University, Prague, Czechia
Supported by project CE-ITI (GAČR no. P202/12/G061) of the Czech Science Foundation.
Dániel
Marx
Dániel Marx
Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI), Budapest, Hungary
Supported by ERC Consolidator Grant SYSTEMATICGRAPH (No. 725978)
10.4230/LIPIcs.SWAT.2018.19
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Andreas E. Feldmann and Daniel Marx
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