Graph and String Parameters: Connections Between Pathwidth, Cutwidth and the Locality Number

Abstract We investigate the locality number, a recently introduced structural parameter for strings (with applications in pattern matching with variables), and its connection to two important graph-parameters, cutwidth and pathwidth. These connections allow us to show that computing the locality number is $$\textsf {NP}$$ NP -hard, but fixed-parameter tractable, if parameterised by the locality number or by the alphabet size, which has been formulated as open problems in the literature. Moreover, the locality number can be approximated with ratio $${{\,\textrm{O}\,}}(\sqrt{\log ({{\,\mathrm{\textsf {opt}}\,}})} \log (n))$$ O ( log ( opt ) log ( n ) ) . An important aspect of our work – that is relevant in its own right and of independent interest – is that we identify connections between the string parameter of the locality number on the one hand, and the famous graph parameters of cutwidth and pathwidth, on the other hand. These two parameters have been jointly investigated in the literature and are arguably among the most central graph parameters that are based on “linearisations” of graphs. In this way, we also identify a direct approximation preserving reduction from cutwidth to pathwidth, which shows that any polynomial $$f({{\,\mathrm{\textsf {opt}}\,}},|V|)$$ f ( opt , | V | ) -approximation algorithm for pathwidth yields a polynomial $$2f(2{{\,\mathrm{\textsf {opt}}\,}},h)$$ 2 f ( 2 opt , h ) -approximation algorithm for cutwidth on multigraphs (where h is the number of edges). In particular, this translates known approximation ratios for pathwidth into new approximation ratios for cutwidth, namely $${{\,\textrm{O}\,}}(\sqrt{\log ({{\,\mathrm{\textsf {opt}}\,}})} \log (h))$$ O ( log ( opt ) log ( h ) ) and $${{\,\textrm{O}\,}}(\sqrt{\log ({{\,\mathrm{\textsf {opt}}\,}})} {{\,\mathrm{\textsf {opt}}\,}})$$ O ( log ( opt ) opt ) for (multi) graphs with h edges.

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Publication Details

Journal
Algorithmica
Published
2026-08-24
DOI
https://doi.org/10.1007/s00453-026-01404-5
Citations
4
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
0.00

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article

Graph and String Parameters: Connections Between Pathwidth, Cutwidth and the Locality Number

Florín Manea, Katrin Casel, Pamela Fleischmann, Markus L. Schmid et al.
4 citations
Algorithmica
Algorithms and Data Compression
article

Graph and String Parameters: Connections Between Pathwidth, Cutwidth and the Locality Number

Florín Manea, Katrin Casel, Pamela Fleischmann, Markus L. Schmid, Tomasz Kociumaka
article en
4 citations

Abstract

Abstract We investigate the locality number, a recently introduced structural parameter for strings (with applications in pattern matching with variables), and its connection to two important graph-parameters, cutwidth and pathwidth. These connections allow us to show that computing the locality number is $$\textsf {NP}$$ NP -hard, but fixed-parameter tractable, if parameterised by the locality number or by the alphabet size, which has been formulated as open problems in the literature. Moreover, the locality number can be approximated with ratio $${{\,\textrm{O}\,}}(\sqrt{\log ({{\,\mathrm{\textsf {opt}}\,}})} \log (n))$$ O ( log ( opt ) log ( n ) ) . An important aspect of our work – that is relevant in its own right and of independent interest – is that we identify connections between the string parameter of the locality number on the one hand, and the famous graph parameters of cutwidth and pathwidth, on the other hand. These two parameters have been jointly investigated in the literature and are arguably among the most central graph parameters that are based on “linearisations” of graphs. In this way, we also identify a direct approximation preserving reduction from cutwidth to pathwidth, which shows that any polynomial $$f({{\,\mathrm{\textsf {opt}}\,}},|V|)$$ f ( opt , | V | ) -approximation algorithm for pathwidth yields a polynomial $$2f(2{{\,\mathrm{\textsf {opt}}\,}},h)$$ 2 f ( 2 opt , h ) -approximation algorithm for cutwidth on multigraphs (where h is the number of edges). In particular, this translates known approximation ratios for pathwidth into new approximation ratios for cutwidth, namely $${{\,\textrm{O}\,}}(\sqrt{\log ({{\,\mathrm{\textsf {opt}}\,}})} \log (h))$$ O ( log ( opt ) log ( h ) ) and $${{\,\textrm{O}\,}}(\sqrt{\log ({{\,\mathrm{\textsf {opt}}\,}})} {{\,\mathrm{\textsf {opt}}\,}})$$ O ( log ( opt ) opt ) for (multi) graphs with h edges.

AlgorithmicaVol. 88(5)
Loughborough University (GB), Christian-Albrechts-Universität zu Kiel (DE), Humboldt-Universität zu Berlin (DE), Max Planck Institute for Informatics (DE), Universitätsmedizin Göttingen (DE), University of Göttingen (DE)
Deutsche Forschungsgemeinschaft, Israel Science Foundation, Humboldt-Universität zu Berlin
Openalex Percentile: Top 100%
Algorithms and Data Compression
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