Bounds for online bin packing with cardinality constraints

József Békési, György Dósa, Leah Epstein

Research output: Contribution to journalArticlepeer-review

Abstract

We study a bin packing problem in which a bin can contain at most k items of total size at most 1, where k≥2 is a given parameter. Items are presented one by one in an online fashion. We analyze the best absolute competitive ratio of the problem and prove tight bounds of 2 for any k≥4. Additionally, we present bounds for relatively small values of k with respect to the asymptotic competitive ratio and the absolute competitive ratio. In particular, we provide tight bounds on the absolute competitive ratio of First Fit for k=2,3,4, and improve the known lower bounds on asymptotic competitive ratios for multiple values of k. Our method for obtaining a lower bound on the asymptotic competitive ratio using a certain type of an input is general, and we also use it to obtain an alternative proof of the known lower bound on the asymptotic competitive ratio of standard online bin packing.

Original languageEnglish
Pages (from-to)190-204
Number of pages15
JournalInformation and Computation
Volume249
DOIs
StatePublished - 1 Aug 2016

Bibliographical note

Funding Information:
Békési was supported by the Austrian–Hungarian Action Foundation (Project number: 91öu2 ). Research of György Dósa was partially supported by the project VKSZ_12-1-2013-0088 Development of cloud based smart IT solutions by IBM Hungary in cooperation with the University of Pannonia .

Publisher Copyright:
© 2016 Elsevier Inc.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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