A Parameterized View on Multi-Layer Cluster Editing

09/26/2017
by   Jiehua Chen, et al.
0

In classical Cluster Editing we seek to transform a given graph into a disjoint union of cliques, called a cluster graph, using the fewest number of edge modifications (deletions or additions). Motivated by recent applications, we propose and study Cluster Editing in multi-layer graphs. A multi-layer graph consists of a set of simple graphs, called layers, that all have the same vertex set. In Multi-Layer Cluster Editing we aim to transform all layers into cluster graphs that differ only slightly. More specifically, we allow to mark at most d vertices and to transform each layer of the multi-layer graph into a cluster graph with at most k edge modifications per layer such that, if we remove the marked vertices, we obtain the same cluster graph in all layers. Multi-Layer Cluster Editing is NP-hard and we analyze its parameterized complexity. We focus on the natural parameters "max. number d of marked vertices", "max. number k of edge modifications per layer", "number n of vertices", and "number l of layers". We fully explore the parameterized computational complexity landscape for those parameters and their combinations. Our main results are that Multi-Layer Cluster Editing is FPT with respect to the parameter combination (d, k) and that it is para-NP-hard for all smaller or incomparable parameter combinations. Furthermore, we give a polynomial kernel with respect to the parameter combination (d, k, l) and show that for all smaller or incomparable parameter combinations, the problem does not admit a polynomial kernel unless NP is in coNP/poly.

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