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shopST: Flexible Job-Shop Scheduling with Agent-Based Simulated Trading

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Multiagent System Technologies (MATES 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10413))

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Abstract

Paradigms in modern production are shifting and pose new demands for optimization techniques. The emergence of new, versatile, reconfigurable and networked machines enables flexible manufacturing scenarios which require, in particular, planning and scheduling methods for cyber-physical production systems to be flexible, reasonably fast, and anytime. This paper presents an approach to flexible job-shop manufacturing scheduling with agent-based simulated trading, called shopST. Aspects of real manufacturing scheduling problems form the basis for a physical decomposition of the planning system into agents. The initial schedule created by the agents in shopST through reactive negotiation is successively improved through the exchange of resource binding constraints with an additional market agent. shopST is evaluated in comparison to selected other different solution approaches to flexible job-shop scheduling.

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Notes

  1. 1.

    The source code for this project is publicly available at https://sourceforge.net/projects/shopst/.

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Acknowledgements

The work described in this paper was partially funded by the German Federal Ministry of Education and Research (BMBF) in the project INVERSIV and the European Commission in the project CREMA.

Author information

Authors and Affiliations

  1. Saarland University, Saarbruecken, Germany

    Frank Yukio Nedwed

  2. German Research Center for Artificial Intelligence (DFKI), Saarbruecken, Germany

    Ingo Zinnikus, Maxat Nukhayev, Matthias Klusch & Luca Mazzola

Authors
  1. Frank Yukio Nedwed
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  2. Ingo Zinnikus
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  3. Maxat Nukhayev
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  4. Matthias Klusch
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  5. Luca Mazzola
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Corresponding author

Correspondence to Matthias Klusch .

Editor information

Editors and Affiliations

  1. University of Trier, Trier, Germany

    Jan Ole Berndt

  2. University of Vienna, Vienna, Austria

    Paolo Petta

  3. Institute for Computer Science and Business Information Systems (ICB), University of Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany

    Rainer Unland

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Nedwed, F.Y., Zinnikus, I., Nukhayev, M., Klusch, M., Mazzola, L. (2017). shopST: Flexible Job-Shop Scheduling with Agent-Based Simulated Trading. In: Berndt, J., Petta, P., Unland, R. (eds) Multiagent System Technologies. MATES 2017. Lecture Notes in Computer Science(), vol 10413. Springer, Cham. https://doi.org/10.1007/978-3-319-64798-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-64798-2_8

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