English

Lower Bounds for Protrusion Replacement by Counting Equivalence Classes

Data Structures and Algorithms 2016-09-30 v1 Discrete Mathematics

Abstract

Garnero et al. [SIAM J. Discrete Math. 2015, 29(4):1864--1894] recently introduced a framework based on dynamic programming to make applications of the protrusion replacement technique constructive and to obtain explicit upper bounds on the involved constants. They show that for several graph problems, for every boundary size tt one can find an explicit set Rt\mathcal{R}_t of representatives. Any subgraph HH with a boundary of size tt can be replaced with a representative HRtH' \in \mathcal{R}_t such that the effect of this replacement on the optimum can be deduced from HH and HH' alone. Their upper bounds on the size of the graphs in Rt\mathcal{R}_t grow triple-exponentially with tt. In this paper we complement their results by lower bounds on the sizes of representatives, in terms of the boundary size tt. For example, we show that each set of planar representatives Rt\mathcal{R}_t for Independent Set or Dominating Set contains a graph with Ω(2t/4t)\Omega(2^t / \sqrt{4t}) vertices. This lower bound even holds for sets that only represent the planar subgraphs of bounded pathwidth. To obtain our results we provide a lower bound on the number of equivalence classes of the canonical equivalence relation for Independent Set on tt-boundaried graphs. We also find an elegant characterization of the number of equivalence classes in general graphs, in terms of the number of monotone functions of a certain kind. Our results show that the number of equivalence classes is at most 22t2^{2^t}, improving on earlier bounds of the form (t+1)2t(t+1)^{2^t}.

Keywords

Cite

@article{arxiv.1609.09304,
  title  = {Lower Bounds for Protrusion Replacement by Counting Equivalence Classes},
  author = {Bart M. P. Jansen and Jules J. H. M. Wulms},
  journal= {arXiv preprint arXiv:1609.09304},
  year   = {2016}
}

Comments

An extended abstract of this work appeared in the proceedings of the 11th International Symposium on Parameterized and Exact Computation (IPEC 2016)

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