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An 8/3 Lower Bound for Online Dynamic Bin Packing

  • Prudence W. H. Wong
  • Fencol C. C. Yung
  • Mihai Burcea
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7676)

Abstract

We study the dynamic bin packing problem introduced by Coffman, Garey and Johnson. This problem is a generalization of the bin packing problem in which items may arrive and depart dynamically. The objective is to minimize the maximum number of bins used over all time. The main result is a lower bound of 8/3 ~2.666 on the achievable competitive ratio, improving the best known 2.5 lower bound. The previous lower bounds were 2.388, 2.428, and 2.5. This moves a big step forward to close the gap between the lower bound and the upper bound, which currently stands at 2.788. The gap is reduced by about 60% from 0.288 to 0.122. The improvement stems from an adversarial sequence that forces an online algorithm \({\mathcal{A}}\) to open 2s bins with items having a total size of s only and this can be adapted appropriately regardless of the current load of other bins that have already been opened by \({\mathcal{A}}\). Comparing with the previous 2.5 lower bound, this basic step gives a better way to derive the complete adversary and a better use of items of slightly different sizes leading to a tighter lower bound. Furthermore, we show that the 2.5-lower bound can be obtained using this basic step in a much simpler way without case analysis.

Keywords

Competitive Ratio Total Load Online Algorithm Item Size Online Setting 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Prudence W. H. Wong
    • 1
  • Fencol C. C. Yung
    • 1
  • Mihai Burcea
    • 1
  1. 1.Department of Computer ScienceUniversity of LiverpoolUK

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