Lower bounds for several online variants of bin packing

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

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

Abstract

We consider several previously studied online variants of bin packing and prove new and improved lower bounds on the asymptotic competitive ratios for them. For that, we use a method of fully adaptive constructions. In particular, we improve the lower bound for the asymptotic competitive ratio of online square packing significantly, raising it from roughly 1.68 to above 1.75.

Original languageEnglish
Title of host publicationApproximation and Online Algorithms - 15th International Workshop, WAOA 2017, Revised Selected Papers
EditorsRoberto Solis-Oba, Rudolf Fleischer
PublisherSpringer Verlag
Pages102-117
Number of pages16
ISBN (Print)9783319894409
DOIs
StatePublished - 2018
Event15th Workshop on Approximation and Online Algorithms, WAOA 2017 - Vienna, Austria
Duration: 7 Sep 20178 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10787 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Workshop on Approximation and Online Algorithms, WAOA 2017
Country/TerritoryAustria
CityVienna
Period7/09/178/09/17

Bibliographical note

Funding Information:
Gy. Dósa was supported by VKSZ 12-1-2013-0088 “Development of cloud based smart IT solutions by IBM Hungary in cooperation with the University of Pannonia” and by National Research, Development and Innovation Office – NKFIH under the grant SNN 116095. L. Epstein and A. Levin were partially supported by a grant from GIF - the German-Israeli Foundation for Scientific Research and Development (grant number I-1366-407.6/2016).

Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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