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        <datestamp>2024-03-06T10:56:43Z</datestamp>
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          <dc:title>Tiling with Squares and Packing Dominos in Polynomial Time</dc:title>
          <dc:creator>Aamand, Anders</dc:creator>
          <dc:creator>Abrahamsen, Mikkel</dc:creator>
          <dc:creator>Ahle, Thomas</dc:creator>
          <dc:creator>Rasmussen, Peter M. R.</dc:creator>
          <dc:subject>packing</dc:subject>
          <dc:subject>tiling</dc:subject>
          <dc:subject>polyominos</dc:subject>
          <dc:description>A polyomino is a polygonal region with axis-parallel edges and corners of integral coordinates, which may have holes. In this paper, we consider planar tiling and packing problems with polyomino pieces and a polyomino container P. We give polynomial-time algorithms for deciding if P can be tiled with k× k squares for any fixed k which can be part of the input (that is, deciding if P is the union of a set of non-overlapping k× k squares) and for packing P with a maximum number of non-overlapping and axis-parallel 2× 1 dominos, allowing rotations by 90^∘. As packing is more general than tiling, the latter algorithm can also be used to decide if P can be tiled by 2× 1 dominos.&#13;
These are classical problems with important applications in VLSI design, and the related problem of finding a maximum packing of 2× 2 squares is known to be NP-hard [J. Algorithms 1990]. For our three problems there are known pseudo-polynomial-time algorithms, that is, algorithms with running times polynomial in the area or perimeter of P. However, the standard, compact way to represent a polygon is by listing the coordinates of the corners in binary. We use this representation, and thus present the first polynomial-time algorithms for the problems. Concretely, we give a simple O(nlog n)-time algorithm for tiling with squares, where n is the number of corners of P. We then give a more involved algorithm that reduces the problems of packing and tiling with dominos to finding a maximum and perfect matching in a graph with O(n³) vertices. This leads to algorithms with running times O(n³(log³ n)/(log²log n)) and O(n³(log² n)/(log log n)), respectively.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Anders Aamand and Mikkel Abrahamsen and Thomas Ahle and Peter M. R. Rasmussen</dc:contributor>
          <dc:date>2022</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 224, 38th International Symposium on Computational Geometry (SoCG 2022)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.SoCG.2022.1</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-160096</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2022.1</dc:identifier>
          <dc:language>eng</dc:language>
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