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        <datestamp>2024-03-06T10:44:22Z</datestamp>
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          <dc:title>Generalized Assignment of Time-Sensitive Item Groups</dc:title>
          <dc:creator>Sarpatwar, Kanthi</dc:creator>
          <dc:creator>Schieber, Baruch</dc:creator>
          <dc:creator>Shachnai, Hadas</dc:creator>
          <dc:subject>Approximation Algorithms</dc:subject>
          <dc:subject>Packing and Covering problems</dc:subject>
          <dc:subject>Generalized Assignment problem</dc:subject>
          <dc:description>We study the generalized assignment problem with time-sensitive item groups (chi-AGAP). It has central applications in advertisement placement on the Internet, and in virtual network embedding in Cloud data centers. We are given a set of items, partitioned into n groups, and a set of T identical bins (or, time-slots). Each group 1 &lt;= j &lt;= n has a time-window chi_j = [r_j, d_j]subseteq [T] in which it can be packed. Each item i in group j has a size s_i&gt;0 and a non-negative utility u_{it} when packed into bin t in chi_j. A bin can accommodate at most one item from each group and the total size of the items in a bin cannot exceed its capacity. The goal is to find a feasible packing of a subset of the items in the bins such that the total utility from groups that are completely packed is maximized. Our main result is an Omega(1)-approximation algorithm for chi-AGAP. Our approximation technique relies on a non-trivial rounding of a configuration LP, which can be adapted to other common scenarios of resource allocation in Cloud data centers.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Kanthi Sarpatwar and Baruch Schieber and Hadas Shachnai</dc:contributor>
          <dc:date>2018</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 116, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX-RANDOM.2018.24</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-94287</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2018.24</dc:identifier>
          <dc:language>eng</dc:language>
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