Lower Bounds for Several Standard Bin Packing Algorithms in the Random Order Model

Leah Epstein, Asaf Levin

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

Abstract

We consider the performance of standard bin packing algorithms in the random order model. We provide an improved lower bound of 1.15582656 on the asymptotic approximation ratio of Best Fit (BF) for randomly ordered inputs. We also show lower bounds on the asymptotic approximation ratio for two bounded space bin packing algorithms in this model, namely for 2-BF and 2-FF. These are well-studied bounded space algorithms and the first one has the same asymptotic worst-case performance as BF. However, the resulting lower bounds on their performances in the random order model are much higher than that of BF.

Original languageEnglish
Title of host publication19th International Symposium on Algorithms and Data Structures, WADS 2025
EditorsPat Morin, Eunjin Oh
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959773980
DOIs
StatePublished - 29 Aug 2025
Event19th International Symposium on Algorithms and Data Structures, WADS 2025 - Toronto, Canada
Duration: 11 Aug 202515 Aug 2025

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume349
ISSN (Print)1868-8969

Conference

Conference19th International Symposium on Algorithms and Data Structures, WADS 2025
Country/TerritoryCanada
CityToronto
Period11/08/2515/08/25

Bibliographical note

Publisher Copyright:
© Leah Epstein and Asaf Levin.

Keywords

  • Best Fit
  • Bin packing
  • Bounded space algorithms
  • Random order

ASJC Scopus subject areas

  • Software

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