The Convergence Time for Selfish Bin Packing

  • György Dósa
  • Leah Epstein
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8768)


In classic bin packing, the objective is to partition a set of n items with positive rational sizes in (0,1] into a minimum number of subsets called bins, such that the total size of the items of each bin at most 1. We study a bin packing game where the cost of each bin is 1, and given a valid packing of the items, each item has a cost associated with it, such that the items that are packed into a bin share its cost equally. We find tight bounds on the exact worst-case number of steps in processes of convergence to pure Nash equilibria. Those are processes that are given an arbitrary packing. As long as there exists an item that can reduce its cost by moving from its bin to another bin, in each step, a controller selects such an item and instructs it to perform such a beneficial move. The process terminates when no further beneficial moves exist. The function of n that we find is Θ(n 3/2), improving the previous bound of Han et al., who showed an upper bound of O(n 2).


Nash Equilibrium Small Step Convergence Time Good Number Congestion Game 
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 2014

Authors and Affiliations

  • György Dósa
    • 1
  • Leah Epstein
    • 2
  1. 1.Department of MathematicsUniversity of PannoniaVeszprémHungary
  2. 2.Department of MathematicsUniversity of HaifaHaifaIsrael

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