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The Lovász-Local-Lemma and Scheduling

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Efficient Approximation and Online Algorithms

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3484))

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Abstract

Probabilistic methods have advanced the design of algorithms in algorithmic discrete mathematics and theoretical computer science. Many notoriously hard algorithmic problems have been solved with randomized algorithms or probabilistic methods, either optimally or in a satisfactory approximative way. One of the powerful tools in analyzing randomized approximation algorithms is the Lovász-Local-Lemma, a sieve method with many nice applications. In this article we show its impact on job shop scheduling and resource constrained scheduling.

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Author information

Authors and Affiliations

  1. Institut für Informatik und Praktische Mathematik, Christian-Albrechts-Universität, zu Kiel, Christian-Albrechts-Platz 4, D-24118, Kiel, Germany

    Anand Srivastav

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  1. Anand Srivastav
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Editors and Affiliations

  1. IBISC, CNRS FRE 3190, Université d’Evry Val d’Essonne, Boulevard François Mitterand, 91025, Evry Cedex, France

    Evripidis Bampis

  2. Institute for Computer Science, University of Kiel, Olshausenstrasse 40, 24118, Kiel, Germany

    Klaus Jansen

  3. Brown University, 02918, Providence, RI, USA

    Claire Kenyon

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© 2006 Springer-Verlag Berlin Heidelberg

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Srivastav, A. (2006). The Lovász-Local-Lemma and Scheduling. In: Bampis, E., Jansen, K., Kenyon, C. (eds) Efficient Approximation and Online Algorithms. Lecture Notes in Computer Science, vol 3484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11671541_11

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  • DOI: https://doi.org/10.1007/11671541_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32212-2

  • Online ISBN: 978-3-540-32213-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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