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        <identifier>oai:drops-oai.dagstuhl.de:11894</identifier>
        <datestamp>2024-03-06T10:48:57Z</datestamp>
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          <dc:title>Asymptotic Quasi-Polynomial Time Approximation Scheme for Resource Minimization for Fire Containment</dc:title>
          <dc:creator>Rahgoshay, Mirmahdi</dc:creator>
          <dc:creator>Salavatipour, Mohammad R.</dc:creator>
          <dc:subject>Firefighter Problem</dc:subject>
          <dc:subject>Resource Management</dc:subject>
          <dc:subject>Fire Containment</dc:subject>
          <dc:subject>Approximation Algorithm</dc:subject>
          <dc:subject>Asymptotic Approximation Scheme</dc:subject>
          <dc:description>Resource Minimization Fire Containment (RMFC) is a natural model for optimal inhibition of harmful spreading phenomena on a graph. In the RMFC problem on trees, we are given an undirected tree G, and a vertex r where the fire starts at, called root. At each time step, the firefighters can protect up to B vertices of the graph while the fire spreads from burning vertices to all their neighbors that have not been protected so far. The task is to find the smallest B that allows for saving all the leaves of the tree. The problem is hard to approximate up to any factor better than 2 even on trees unless P = NP [King and MacGillivray, 2010].&#13;
Chalermsook and Chuzhoy [Chalermsook and Chuzhoy, 2010] presented a Linear Programming based O(log^* n) approximation for RMFC on trees that matches the integrality gap of the natural Linear Programming relaxation. This was recently improved by Adjiashvili, Baggio, and Zenklusen [Adjiashvili et al., 2017] to a 12-approximation through a combination of LP rounding along with several new techniques.&#13;
In this paper we present an asymptotic QPTAS for RMFC on trees. More specifically, let ε&gt;0, and ℐ be an instance of RMFC where the optimum number of firefighters to save all the leaves is OPT(ℐ). We present an algorithm which uses at most ⌈(1+ε)OPT(ℐ)⌉ many firefighters at each time step and runs in time n^O(log log n/ε). This suggests that the existence of an asymptotic PTAS is plausible especially since the exponent is O(log log n), not O(log n).&#13;
Our result combines a more powerful height reduction lemma than the one in [Adjiashvili et al., 2017] with LP rounding and dynamic programming to find the solution. We also apply our height reduction lemma to the algorithm provided in [Adjiashvili et al., 2017] plus a more careful analysis to improve their 12-approximation and provide a polynomial time (5+ε)-approximation.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Mirmahdi Rahgoshay and Mohammad R. Salavatipour</dc:contributor>
          <dc:date>2020</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 154, 37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.STACS.2020.33</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-118946</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2020.33</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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