Online Bin Packing with Advice of Small Size

  • Spyros Angelopoulos
  • Christoph Dürr
  • Shahin Kamali
  • Marc P. Renault
  • Adi Rosén
Article
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Abstract

In this paper, we study the advice complexity of the online bin packing problem. In this well-studied setting, the online algorithm is supplemented with some additional information concerning the input. We improve upon both known upper and lower bounds of online algorithms for this problem. On the positive side, we first provide a relatively simple algorithm that achieves a competitive ratio arbitrarily close to 1.5, using constant-size advice. Our result implies that 16 bits of advice suffice to obtain a competitive ratio better than any online algorithm without advice, thus improving the previously known bound of O(log(n)) bits required to attain this performance. In addition, we introduce a more complex algorithm that still requires only constant-size advice, and has a competitive ratio arbitrarily close to 1.47012. This is the currently best performance of any online bin packing algorithm with sublinear advice. On the negative side, we extend a construction due to Boyar et al. (Algorithmica 74(1), 507–527 2016) so as to show that no online algorithm with sub-linear advice can be 7/6-competitive, improving on the lower bound of 9/8 from Boyar et al.

Keywords

Online bin packing Competitive analysis Advice complexity 
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Notes

Acknowledgments

Research supported in part by project ANR-11-BS02-0015 “New Techniques in Online Computation–NeTOC”. A preliminary version of this paper appeared in the Proceedings of the 14th International Symposium on Algorithms and Data Structures (WADS), 2015 [2].

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Spyros Angelopoulos
    • 1
  • Christoph Dürr
    • 1
  • Shahin Kamali
    • 2
  • Marc P. Renault
    • 3
  • Adi Rosén
    • 4
    • 5
  1. 1.Laboratoire d’informatique de Paris-6, LIP6Sorbonne UniversitéParisFrance
  2. 2.Department of Computer ScienceUniversity of ManitobaWinnipegCanada
  3. 3.Department of Computer ScienceUniversity of WisconsinMadisonUSA
  4. 4.CNRSParisFrance
  5. 5.Université Paris DiderotParisFrance

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