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        <identifier>oai:drops-oai.dagstuhl.de:24381</identifier>
        <datestamp>2025-12-12T15:01:16Z</datestamp>
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          <dc:title>A Polynomial-Time Approximation Algorithm for Complete Interval Minors</dc:title>
          <dc:creator>Bourneuf, Romain</dc:creator>
          <dc:creator>Cocquet, Julien</dc:creator>
          <dc:creator>Tang, Chaoliang</dc:creator>
          <dc:creator>Thomassé, Stéphan</dc:creator>
          <dc:subject>Approximation algorithm</dc:subject>
          <dc:subject>Ordered graphs</dc:subject>
          <dc:subject>Interval minors</dc:subject>
          <dc:subject>Delayed decompositions</dc:subject>
          <dc:description>As shown by Robertson and Seymour, deciding whether the complete graph K_t is a minor of an input graph G is a fixed parameter tractable problem when parameterized by t. From the approximation viewpoint, a substantial gap remains: there is no PTAS for finding the largest complete minor unless P = NP, whereas the best known result is a polytime O(√ n)-approximation algorithm by Alon, Lingas and Wahlén.&#13;
We investigate the complexity of finding K_t as interval minor in ordered graphs (i.e. graphs with a linear order on the vertices, in which intervals are contracted to form minors). Our main result is a polytime f(t)-approximation algorithm, where f is triply exponential in t but independent of n. The algorithm is based on delayed decompositions and shows that ordered graphs without a K_t interval minor can be constructed via a bounded number of three operations: closure under substitutions, edge union, and concatenation of a stable set. As a byproduct, graphs avoiding K_t as an interval minor have bounded chromatic number.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Romain Bourneuf and Julien Cocquet and Chaoliang Tang and Stéphan Thomassé</dc:contributor>
          <dc:date>2025</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX/RANDOM.2025.15</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-243814</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.15</dc:identifier>
          <dc:language>eng</dc:language>
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