Skip to main content
Log in

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

  • Conference paper

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

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, books and news in related subjects, suggested using machine learning.

References

  1. Foster, I., Kesselman, C.: The Anatomy of the Grid: Enabling Scalable Virtual Organisations. Int. J. of Supercomputer Applications 15(3), 200–222 (2001)

  2. Brucker, P.: Scheduling Algorithms. Springer, Berlin (2004)

  3. Setamaa-Karkkainen, A., Miettinen, K., Vuori, J.: Best Compromise Solution for a New Multiobjective Scheduling Problem. Computers & OR 33(8), 2353–2368 (2006)

  4. Brucker, P., Knust, S.: Complex Scheduling. Springer, Berlin (2006)

  5. Giffler, B., Thompson, G.L.: Algorithms for Solving Production Scheduling Problems. Operations Research 8, 487–503 (1960)

  6. Neumann, K., Morlock, M.: Operations Research. Carl Hanser, München (2002)

  7. Süß, W., Quinte, A., Jakob, W., Stucky, K.-U.: Construction of Benchmarks for Comparison of Grid Resource Planning Algorithms. In: Filipe, J., et al. (eds.) Conf. Proc. ICSOFT 2007, vol. PL, Inst.f. Systems and Techn. of Information, Control and Com., pp. 80–87 (2007)

  8. Blume, C., Jakob, W.: GLEAM – An Evolutionary Algorithm for Planning and Control Based on Evolution Strategy. In: Conf. Proc. GECCO 2002, Late Breaking Papers (2002)

  9. Davis, L. (ed.): Handbook of Genetic Algorithms. V. Nostrand Reinhold, New York (1991)

  10. Bierwirth, C., Mattfeld, D.C., Kopfer, H.: On Permutation Representations for Scheduling Problems. In: Voigt, H.-M., et al. (eds.) PPSN IV, vol. 1141, pp. 310–318. Springer, Heidelberg (1996)

Download references

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
  2. Alexander Quinte
  3. Karl-Uwe Stucky
  4. Wolfgang Süß

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

About this paper

Cite this paper

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

Download citation

  • 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 Science Computer Science (R0)

Keywords

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Publish with us

Policies and ethics

AltStyle によって変換されたページ (->オリジナル) /