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Approximation Algorithms for Demand Strip Packing

Authors Waldo Gálvez , Fabrizio Grandoni, Afrouz Jabal Ameli, Kamyar Khodamoradi

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Author Details

Waldo Gálvez
  • Technische Universität München, Germany
Fabrizio Grandoni
  • IDSIA, USI-SUPSI, Lugano, Switzerland
Afrouz Jabal Ameli
  • IDSIA, USI-SUPSI, Lugano, Switzerland
Kamyar Khodamoradi
  • Universitä Würzburg, Germany

Funding

  • Gálvez, Waldo: Supported by the European Research Council, Grant Agreement No. 691672, project APEG.
  • Grandoni, Fabrizio: Partially supported by the SNF Excellence Grant 200020B_182865.
  • Ameli, Afrouz Jabal: Partially supported by the SNF Excellence Grant 200020B_182865.
  • Khodamoradi, Kamyar: Partially supported by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project number 399223600. This project was carried out in part when the author was a postdoctoral researcher at IDSIA, USI-SUPSI, Switzerland.

Cite AsGet BibTex

Waldo Gálvez, Fabrizio Grandoni, Afrouz Jabal Ameli, and Kamyar Khodamoradi. Approximation Algorithms for Demand Strip Packing. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 207, pp. 20:1-20:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2021.20

Abstract

In the Demand Strip Packing problem (DSP), we are given a time interval and a collection of tasks, each characterized by a processing time and a demand for a given resource (such as electricity, computational power, etc.). A feasible solution consists of a schedule of the tasks within the mentioned time interval. Our goal is to minimize the peak resource consumption, i.e. the maximum total demand of tasks executed at any point in time. It is known that DSP is NP-hard to approximate below a factor 3/2, and standard techniques for related problems imply a (polynomial-time) 2-approximation. Our main result is a (5/3+ε)-approximation algorithm for any constant ε > 0. We also achieve best-possible approximation factors for some relevant special cases.

Subject Classification

ACM Subject Classification
  • Theory of computation → Packing and covering problems
  • Theory of computation → Scheduling algorithms
Keywords
  • Strip Packing
  • Two-Dimensional Packing
  • Approximation Algorithms

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