A New Lower Bound for Classic Online Bin Packing

János Balogh, József Békési, György Dósa, Leah Epstein, Asaf Levin

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


We improve the lower bound on the asymptotic competitive ratio of any online algorithm for bin packing to above 1.54278. We demonstrate for the first time the advantage of branching and the applicability of full adaptivity in the design of lower bounds for the classic online bin packing problem. We apply a new method for weight based analysis, which is usually applied only in proofs of upper bounds. The values of previous lower bounds were approximately 1.5401 and 1.5403.

Original languageEnglish
Title of host publicationApproximation and Online Algorithms - 17th International Workshop, WAOA 2019, Revised Selected Papers
EditorsEvripidis Bampis, Nicole Megow
Number of pages11
ISBN (Print)9783030394783
StatePublished - 2020
Event17th International Workshop on Approximation and Online Algorithms, WAOA 2019 - Munich, Germany
Duration: 12 Sep 201913 Sep 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11926 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Workshop on Approximation and Online Algorithms, WAOA 2019

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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