Abstract
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 language | English |
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Title of host publication | Approximation and Online Algorithms - 17th International Workshop, WAOA 2019, Revised Selected Papers |
Editors | Evripidis Bampis, Nicole Megow |
Publisher | Springer |
Pages | 18-28 |
Number of pages | 11 |
ISBN (Print) | 9783030394783 |
DOIs | |
State | Published - 2020 |
Event | 17th International Workshop on Approximation and Online Algorithms, WAOA 2019 - Munich, Germany Duration: 12 Sep 2019 → 13 Sep 2019 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11926 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 17th International Workshop on Approximation and Online Algorithms, WAOA 2019 |
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Country/Territory | Germany |
City | Munich |
Period | 12/09/19 → 13/09/19 |
Bibliographical note
Publisher Copyright:© 2020, Springer Nature Switzerland AG.
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science