Random-order bin packing

Edward G. Coffman, János Csirik, Lajos Rónyai, Ambrus Zsbán

Research output: Article

12 Citations (Scopus)

Abstract

The average-case analysis of algorithms usually assumes independent, identical distributions for the inputs. In [C. Kenyon, Best-fit bin-packing with random order, in: Proc. of the Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, SIAM, 1996, pp. 359-364] Kenyon introduced the random-order ratio, a new average-case performance metric for bin packing heuristics, and gave upper and lower bounds for it for the Best Fit heuristics. We introduce an alternative definition of the random-order ratio and show that the two definitions give the same result for Next Fit. We also show that the random-order ratio of Next Fit equals to its asymptotic worst-case, i.e., it is 2.

Original languageEnglish
Pages (from-to)2810-2816
Number of pages7
JournalDiscrete Applied Mathematics
Volume156
Issue number14
DOIs
Publication statusPublished - júl. 28 2008

ASJC Scopus subject areas

  • Discrete Mathematics and Combinatorics
  • Applied Mathematics

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