Black and white bin packing

János Balogh, József Békési, G. Dósa, Hans Kellerer, Z. Tuza

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

We introduce the following version of bin packing. The items are of two types (black and white), and in each bin the item types must alternate. We mostly investigate the online scenario. We study the competitiveness of some classical algorithms (First/Best/Worst/Next Fit, Harmonic) - they do not perform very well - and for all online algorithms we also prove the universal lower bound 1 + 1/2 ln 2 ≈ 1.7213 which significantly exceeds the known upper bound 1.58889 on classical online bin packing. We also design an online algorithm which is 3-competitive in the absolute sense. A 2.5-approximation algorithm and an APTAS is also given for the offline version.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages131-144
Number of pages14
Volume7846 LNCS
DOIs
Publication statusPublished - 2013
Event10th International Workshop on Approximation and Online Algorithms, WAOA 2012 - Ljubljana, Slovenia
Duration: Sep 13 2012Sep 14 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7846 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Workshop on Approximation and Online Algorithms, WAOA 2012
CountrySlovenia
CityLjubljana
Period9/13/129/14/12

Fingerprint

Bin Packing
Online Algorithms
Bins
Competitiveness
Alternate
Approximation Algorithms
Exceed
Harmonic
Approximation algorithms
Lower bound
Upper bound
Scenarios
Design

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Balogh, J., Békési, J., Dósa, G., Kellerer, H., & Tuza, Z. (2013). Black and white bin packing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7846 LNCS, pp. 131-144). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7846 LNCS). https://doi.org/10.1007/978-3-642-38016-7_12

Black and white bin packing. / Balogh, János; Békési, József; Dósa, G.; Kellerer, Hans; Tuza, Z.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7846 LNCS 2013. p. 131-144 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7846 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Balogh, J, Békési, J, Dósa, G, Kellerer, H & Tuza, Z 2013, Black and white bin packing. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7846 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7846 LNCS, pp. 131-144, 10th International Workshop on Approximation and Online Algorithms, WAOA 2012, Ljubljana, Slovenia, 9/13/12. https://doi.org/10.1007/978-3-642-38016-7_12
Balogh J, Békési J, Dósa G, Kellerer H, Tuza Z. Black and white bin packing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7846 LNCS. 2013. p. 131-144. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-38016-7_12
Balogh, János ; Békési, József ; Dósa, G. ; Kellerer, Hans ; Tuza, Z. / Black and white bin packing. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7846 LNCS 2013. pp. 131-144 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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