A New Lower Bound for Classic Online Bin Packing

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

doi:10.1007/s00453-021-00818-7

A New Lower Bound for Classic Online Bin Packing

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

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

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
Pages (from-to)	2047-2062
Number of pages	16
Journal	Algorithmica
Volume	83
Issue number	7
DOIs	https://doi.org/10.1007/s00453-021-00818-7
State	Published - Jul 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

ASJC Scopus subject areas

General Computer Science
Computer Science Applications
Applied Mathematics

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10.1007/s00453-021-00818-7

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AU - Epstein, Leah

AU - Levin, Asaf

PY - 2021/7

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AB - 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.

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A New Lower Bound for Classic Online Bin Packing

Abstract

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ASJC Scopus subject areas

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