Resource augmentation for online bounded space bin packing (Extended abstract)

  • J. Csirik
  • , G.J. Woeginger

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    10 Citations (Scopus)

    Abstract

    We study online bounded space bin packing in the resource augmentation model of competitive analysis. In this model, the online bounded space packing algorithm has to pack a list L of items in (0,1] into a small number of bins of size b = 1. Its performance is measured by comparing the produced packing against the optimal offline packing of the list L into bins of size 1. We present a complete solution to this problem: For every bin size b = 1, we design online bounded space bin packing algorithms whose worst case ratio in this model comes arbitrarily close to a certain bound ¿(b). Moreover, we prove that no online bounded space algorithm can perform better than ¿(b) in the worst case.
    Original languageEnglish
    Title of host publicationAutomata, Languages and Programming (Proceedings 27th International Colloquium, ICALP 2000, Geneva, Switzerland, July 9-15, 2000)
    EditorsU. Montanari, J.D.P. Rolim, W. Welzl
    Place of PublicationBerlin
    PublisherSpringer
    Pages296-304
    ISBN (Print)3-540-67715-1
    DOIs
    Publication statusPublished - 2000

    Publication series

    NameLecture Notes in Computer Science
    Volume1853
    ISSN (Print)0302-9743

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