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Improved Pseudo-Polynomial-Time Approximation for Strip Packing

Authors Waldo Gálvez, Fabrizio Grandoni, Salvatore Ingala, Arindam Khan

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Waldo Gálvez
Fabrizio Grandoni
Salvatore Ingala
Arindam Khan

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Waldo Gálvez, Fabrizio Grandoni, Salvatore Ingala, and Arindam Khan. Improved Pseudo-Polynomial-Time Approximation for Strip Packing. In 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 65, pp. 9:1-9:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2016)


We study the strip packing problem, a classical packing problem which generalizes both bin packing and makespan minimization. Here we are given a set of axis-parallel rectangles in the two-dimensional plane and the goal is to pack them in a vertical strip of fixed width such that the height of the obtained packing is minimized. The packing must be non-overlapping and the rectangles cannot be rotated. A reduction from the partition problem shows that no approximation better than 3/2 is possible for strip packing in polynomial time (assuming P!=NP). Nadiradze and Wiese [SODA16] overcame this barrier by presenting a (7/5+epsilon)-approximation algorithm in pseudo-polynomial-time (PPT). As the problem is strongly NP-hard, it does not admit an exact PPT algorithm (though a PPT approximation scheme might exist). In this paper we make further progress on the PPT approximability of strip packing, by presenting a (4/3+epsilon)-approximation algorithm. Our result is based on a non-trivial repacking of some rectangles in the "empty space" left by the construction by Nadiradze and Wiese, and in some sense pushes their approach to its limit. Our PPT algorithm can be adapted to the case where we are allowed to rotate the rectangles by 90 degrees, achieving the same approximation factor and breaking the polynomial-time approximation barrier of 3/2 for the case with rotations as well.
  • approximation algorithms
  • strip packing
  • rectangle packing
  • cutting-stock problem


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