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        <identifier>oai:drops-oai.dagstuhl.de:13406</identifier>
        <datestamp>2024-03-06T10:51:54Z</datestamp>
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          <dc:title>Towards Constant-Factor Approximation for Chordal / Distance-Hereditary Vertex Deletion</dc:title>
          <dc:creator>Ahn, Jungho</dc:creator>
          <dc:creator>Kim, Eun Jung</dc:creator>
          <dc:creator>Lee, Euiwoong</dc:creator>
          <dc:subject>ptolemaic</dc:subject>
          <dc:subject>approximation algorithm</dc:subject>
          <dc:subject>linear programming</dc:subject>
          <dc:subject>feedback vertex set</dc:subject>
          <dc:description>For a family of graphs ℱ, Weighted ℱ-Deletion is the problem for which the input is a vertex weighted graph G = (V, E) and the goal is to delete S ⊆ V with minimum weight such that G⧵S ∈ ℱ. Designing a constant-factor approximation algorithm for large subclasses of perfect graphs has been an interesting research direction. Block graphs, 3-leaf power graphs, and interval graphs are known to admit constant-factor approximation algorithms, but the question is open for chordal graphs and distance-hereditary graphs.&#13;
In this paper, we add one more class to this list by presenting a constant-factor approximation algorithm when ℱ is the intersection of chordal graphs and distance-hereditary graphs. They are known as ptolemaic graphs and form a superset of both block graphs and 3-leaf power graphs above. Our proof presents new properties and algorithmic results on inter-clique digraphs as well as an approximation algorithm for a variant of Feedback Vertex Set that exploits this relationship (named Feedback Vertex Set with Precedence Constraints), each of which may be of independent interest.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Jungho Ahn and Eun Jung Kim and Euiwoong Lee</dc:contributor>
          <dc:date>2020</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 181, 31st International Symposium on Algorithms and Computation (ISAAC 2020)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.ISAAC.2020.62</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-134063</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2020.62</dc:identifier>
          <dc:language>eng</dc:language>
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