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Measuring what Matters: A Hybrid Approach to Dynamic Programming with Treewidth

Authors Eduard Eiben , Robert Ganian, Thekla Hamm, O-joung Kwon

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LIPIcs.MFCS.2019.42.pdf
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Subject Classification

ACM Subject Classification
  • Theory of computation → Parameterized complexity and exact algorithms
Keywords
  • Parameterized complexity
  • treewidth
  • rank-width
  • fixed-parameter algorithms

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Abstract

We develop a framework for applying treewidth-based dynamic programming on graphs with "hybrid structure", i.e., with parts that may not have small treewidth but instead possess other structural properties. Informally, this is achieved by defining a refinement of treewidth which only considers parts of the graph that do not belong to a pre-specified tractable graph class. Our approach allows us to not only generalize existing fixed-parameter algorithms exploiting treewidth, but also fixed-parameter algorithms which use the size of a modulator as their parameter. As the flagship application of our framework, we obtain a parameter that combines treewidth and rank-width to obtain fixed-parameter algorithms for Chromatic Number, Hamiltonian Cycle, and Max-Cut.

Cite As Get BibTex

Eduard Eiben, Robert Ganian, Thekla Hamm, and O-joung Kwon. Measuring what Matters: A Hybrid Approach to Dynamic Programming with Treewidth. In 44th International Symposium on Mathematical Foundations of Computer Science (MFCS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 138, pp. 42:1-42:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.MFCS.2019.42

Author Details

Eduard Eiben
  • Department of Informatics, University of Bergen, Bergen, Norway
Robert Ganian
  • Vienna University of Technology, Vienna, Austria
Thekla Hamm
  • Vienna University of Technology, Vienna, Austria
O-joung Kwon
  • Department of Mathematics, Incheon National University, Korea

Funding

E. Eiben was supported by Pareto-Optimal Parameterized Algorithms (ERC Starting Grant 715744). R. Ganian acknowledges support by the Austrian Grant Agency (FWF, project P31336 NFPC), and is also affiliated with FI MUNI, Czech Republic. O. Kwon was supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Education (No. NRF-2018R1D1A1B07050294).

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