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        <identifier>oai:drops-oai.dagstuhl.de:19432</identifier>
        <datestamp>2024-03-06T11:04:02Z</datestamp>
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          <dc:title>Budgeted Matroid Maximization: a Parameterized Viewpoint</dc:title>
          <dc:creator>Doron-Arad, Ilan</dc:creator>
          <dc:creator>Kulik, Ariel</dc:creator>
          <dc:creator>Shachnai, Hadas</dc:creator>
          <dc:subject>budgeted matching</dc:subject>
          <dc:subject>budgeted matroid intersection</dc:subject>
          <dc:subject>knapsack problems</dc:subject>
          <dc:subject>FPT-approximation scheme</dc:subject>
          <dc:description>We study budgeted variants of well known maximization problems with multiple matroid constraints. Given an 𝓁-matchoid ℳ on a ground set E, a profit function p:E → ℝ_{≥ 0}, a cost function c:E → ℝ_{≥ 0}, and a budget B ∈ ℝ_{≥ 0}, the goal is to find in the 𝓁-matchoid a feasible set S of maximum profit p(S) subject to the budget constraint, i.e., c(S) ≤ B. The budgeted 𝓁-matchoid (BM) problem includes as special cases budgeted 𝓁-dimensional matching and budgeted 𝓁-matroid intersection. A strong motivation for studying BM from parameterized viewpoint comes from the APX-hardness of unbudgeted 𝓁-dimensional matching (i.e., B = ∞) already for 𝓁 = 3. Nevertheless, while there are known FPT algorithms for the unbudgeted variants of the above problems, the budgeted variants are studied here for the first time through the lens of parameterized complexity.&#13;
We show that BM parametrized by solution size is W[1]-hard, already with a degenerate single matroid constraint. Thus, an exact parameterized algorithm is unlikely to exist, motivating the study of FPT-approximation schemes (FPAS). Our main result is an FPAS for BM (implying an FPAS for 𝓁-dimensional matching and budgeted 𝓁-matroid intersection), relying on the notion of representative set - a small cardinality subset of elements which preserves the optimum up to a small factor. We also give a lower bound on the minimum possible size of a representative set which can be computed in polynomial time.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Ilan Doron-Arad and Ariel Kulik and Hadas Shachnai</dc:contributor>
          <dc:date>2023</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 285, 18th International Symposium on Parameterized and Exact Computation (IPEC 2023)</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.IPEC.2023.13</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-194329</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.IPEC.2023.13</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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