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On-line Bin-Stretching

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Book cover Randomization and Approximation Techniques in Computer Science (RANDOM 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1518))

Abstract

We are given a sequence of items that can be packed into m unit size bins. In the classical bin packing problem we fix the size of the bins and try to pack the items in the minimum number of such bins. In contrast, in the bin-stretching problem we fix the number of bins and try to pack the items while stretching the size of the bins as least as possible. We present two on-line algorithms for the bin-stretching problem that guarantee a stretching factor of 5/3 for any number m of bins. We then combine the two algorithms and design an algorithm whose stretching factor is 1.625 for any m. The analysis for the performance of this algorithm is tight. The best lower bound for any algorithm is 4/3 for any m ≧ 2. We note that the bin-stretching problem is also equivalent to the classical scheduling (load balancing) problem in which the value of the makespan (maximum load) is known in advance.

Research supported in part by the Israel Science Foundation and by the United States-Israel Binational Science Foundation (BSF).

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, Tel-Aviv University, Tel-Aviv, 69978, Israel

    Yossi Azar

  2. Dept. of Computer Science, Tel-Aviv University, Tel-Aviv, 69978, Israel

    Oded Regev

Authors
  1. Yossi Azar
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  2. Oded Regev
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Editor information

Editors and Affiliations

  1. International Computer Science Institute, 1947 Center Street, Suite 600, Berkeley, CA, 94704-1198, USA

    Michael Luby

  2. Computer Science Department, University of Geneva, 24, rue Général Dufour, CH-1211, Geneva 4, Switzerland

    José D. P. Rolim

  3. University of Barcelona (UPC), Jordi Girona Salgado 1-3, E-08034, Barcelona, Spain

    Maria Serna

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© 1998 Springer-Verlag Berlin Heidelberg

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Azar, Y., Regev, O. (1998). On-line Bin-Stretching. In: Luby, M., Rolim, J.D.P., Serna, M. (eds) Randomization and Approximation Techniques in Computer Science. RANDOM 1998. Lecture Notes in Computer Science, vol 1518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49543-6_7

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  • DOI: https://doi.org/10.1007/3-540-49543-6_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65142-0

  • Online ISBN: 978-3-540-49543-7

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