A New Lower Bound for Classic Online Bin Packing

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

doi:https://doi.org/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

Technion - Israel Institute of Technology, University of Haifa

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

All Science Journal Classification (ASJC) codes

General Computer Science
Applied Mathematics
Computer Science Applications

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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.",

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AU - Epstein, Leah

AU - Levin, Asaf

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Y1 - 2021/7

N2 - 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.

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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DO - https://doi.org/10.1007/s00453-021-00818-7

M3 - مقالة

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VL - 83

SP - 2047

EP - 2062

JO - Algorithmica

JF - Algorithmica

IS - 7

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A New Lower Bound for Classic Online Bin Packing

Abstract

All Science Journal Classification (ASJC) codes

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