Treffer: XNLP-Completeness for Parameterized Problems on Graphs with a Linear Structure: XNLP-completeness for parameterized problems on graphs with a linear structure
8:1-8:18
Algorithmica
17th International Symposium on Parameterized and Exact Computation (IPEC 2022)
IPEC
0178-4617
https://research-portal.uu.nl/en/publications/df89aedd-7a2e-4055-938c-d21b56bced16
https://doi.org/10.1007/s00453-024-01274-9
https://hdl.handle.net/11250/3041006
https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.IPEC.2022.8
https://dspace.library.uu.nl/handle/1874/425595
https://hdl.handle.net/11250/3170553
arXiv Non-Exclusive Distribution
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In this paper, we showcase the class XNLP as a natural place for many hard problems parameterized by linear width measures. This strengthens existing W[1]-hardness proofs for these problems, since XNLP-hardness implies W[t]-hardness for all t. It also indicates, via a conjecture by Pilipczuk and Wrochna (ACM Trans Comput Theory 9:1–36, 2018), that any XP algorithm for such problems is likely to require XP space. In particular, we show XNLP-completeness for natural problems parameterized by pathwidth, linear clique-width, and linear mim-width. The problems we consider are Independent Set, Dominating Set, Odd Cycle Transversal, ( q -)Coloring, Max Cut, Maximum Regular Induced Subgraph, Feedback Vertex Set, Capacitated (Red-Blue) Dominating Set, Capacitated Vertex Cover and Bipartite Bandwidth.