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Approximation Algorithms for Flexible Job Shop Problems

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LATIN 2000: Theoretical Informatics (LATIN 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1776))

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Abstract

The Flexible Job Shop Problem is a generalization of the classical job shop scheduling problem in which for every operation there is a group of machines that can process it. The problem is to assign operations to machines and to order the operations on the machines, so that the operations can be processed in the smallest amount of time. We present a linear time approximation scheme for the non-preemptive version of the problem when the number m of machines and the maximum number μ of operations per job are fixed. We also study the preemptive version of the problem when m and μ are fixed, and present a linear time (2 + ε)-approximation algorithm for the problem with migration.

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Author information

Authors and Affiliations

  1. Institut für Informatik und Praktische Mathematik, Universität zu Kiel, Germany

    Klaus Jansen

  2. IDSIA Lugano, Switzerland

    Monaldo Mastrolilli

  3. Department of Computer Science, The University of Western Ontario, Canada

    Roberto Solis-Oba

Authors
  1. Klaus Jansen
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  2. Monaldo Mastrolilli
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  3. Roberto Solis-Oba
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Editor information

Editors and Affiliations

  1. ETH Zurich, Institute of Computational Science, CH-8092 Zurich and, Swiss Institute of Bioinformatics, Switzerland

    Gaston H. Gonnet

  2. Pedeciba Informática, Casilla de Correo 16120, Distrito 6, Montevideo, Uruguay

    Alfredo Viola

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© 2000 Springer-Verlag Berlin Heidelberg

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Jansen, K., Mastrolilli, M., Solis-Oba, R. (2000). Approximation Algorithms for Flexible Job Shop Problems. In: Gonnet, G.H., Viola, A. (eds) LATIN 2000: Theoretical Informatics. LATIN 2000. Lecture Notes in Computer Science, vol 1776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10719839_7

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  • DOI: https://doi.org/10.1007/10719839_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67306-4

  • Online ISBN: 978-3-540-46415-0

  • eBook Packages: Springer Book Archive

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