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Fast Multi-objective Scheduling of Jobs to Constrained Resources Using a Hybrid Evolutionary Algorithm

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Parallel Problem Solving from Nature – PPSN X (PPSN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5199))

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Abstract

The problem tackled here combines three properties of scheduling tasks, each of which makes the basic task more challenging: job scheduling with precedence rules, co-allocation of restricted resources of different performances and costs, and a multi-objective fitness function. As the algorithm must come up with results within a few minutes runtime, EA techniques must be tuned to this limitation. The paper describes how this was achieved and compares the results with a common scheduling algorithm, the Giffler-Thompson procedure.

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Author information

Authors and Affiliations

  1. Forschungszentrum Karlsruhe GmbH, Institute for Applied Computer Science, P.O. Box 3640, 76021, Karlsruhe, Germany

    Wilfried Jakob, Alexander Quinte, Karl-Uwe Stucky & Wolfgang Süß

Authors
  1. Wilfried Jakob
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  2. Alexander Quinte
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  3. Karl-Uwe Stucky
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  4. Wolfgang Süß
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Editor information

Editors and Affiliations

  1. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Günter Rudolph

  2. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Thomas Jansen  & Nicola Beume  & 

  3. Department of Computing and Electronic Systems, University of Essex, CO4 3SQ, Colchester, Essex, UK

    Simon Lucas

  4. Dipartimento di Ingegneria Meccanica, Università degli Studi di Trieste, 34127, Trieste, Italy

    Carlo Poloni

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© 2008 Springer-Verlag Berlin Heidelberg

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Jakob, W., Quinte, A., Stucky, KU., Süß, W. (2008). Fast Multi-objective Scheduling of Jobs to Constrained Resources Using a Hybrid Evolutionary Algorithm. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_102

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  • DOI: https://doi.org/10.1007/978-3-540-87700-4_102

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87699-1

  • Online ISBN: 978-3-540-87700-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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