On Dynamic Bin Packing: An Improved Lower Bound and Resource Augmentation Analysis

  • Wun-Tat Chan
  • Prudence W. H. Wong
  • Fencol C. C. Yung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4112)


We study the dynamic bin packing problem introduced by Coffman, Garey and Johnson [7]. This problem is a generalization of the bin packing problem in which items may arrive and depart from the packing dynamically. The main result in this paper is a lower bound of 2.5 on the achievable competitive ratio, improving the best known 2.428 lower bound [3], and revealing that packing items of restricted form like unit fractions (i.e., of size 1/k for some integer k), which can guarantee a competitive ratio 2.4985 [3], is indeed easier.

We also investigate the resource augmentation analysis on the problem where the on-line algorithm can use bins of size b (> 1) times that of the optimal off-line algorithm. An interesting result is that we prove b = 2 is both necessary and sufficient for the on-line algorithm to match the performance of the optimal off-line algorithm, i.e., achieve 1-competitiveness. Further analysis is made to give a trade-off between the bin size multiplier b and the achievable competitive ratio.


Competitive Ratio Item Size Resource Augmentation Harmonic Algorithm Average Case Behavior 
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 2006

Authors and Affiliations

  • Wun-Tat Chan
    • 1
  • Prudence W. H. Wong
    • 2
  • Fencol C. C. Yung
    • 1
  1. 1.Department of Computer ScienceUniversity of Hong KongHong Kong
  2. 2.Department of Computer ScienceUniversity of LiverpoolUK

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