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A classification pattern for autonomous control methods in logistics

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Logistics Research

Abstract

Autonomous control in logistics enables single logistics objects to control the production and transportation process. This shift from central planning to decentralized control in real-time offers many possibilities to cope with highly dynamic and complex systems. The algorithms that define the decision behavior of each logistics object, autonomous control methods, play a key role in the successful implementation of autonomous control in logistics systems. A transparent classification is needed in order to identify the basic elements these methods consist of. This classification supports the evaluation of autonomous control methods in terms of gaining knowledge about which method characteristics are responsible for a method’s performance. This paper defines what autonomous control methods are, works out their fundamental characteristics, presents multiple methods developed so far, and compares these methods regarding characteristics and performance.

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Acknowledgments

This research is funded by the German Research Foundation (DFG) as part of the Collaborative Research Center 637 Autonomous Cooperating Logistic Processes—A Paradigm Shift and its Limitations (SFB 637) at Bremen University and at Jacobs University Bremen.

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Authors and Affiliations

  1. Global Production Logistics, School of Engineering and Science, Jacobs University Bremen gGmbH, Campus Ring 1, 28759, Bremen, Germany

    Katja Windt, Till Becker & Oliver Jeken

  2. Computational Laboratory for Analysis, Modeling, and Visualization, School of Engineering and Science, Jacobs University Bremen gGmbH, Campus Ring 1, 28759, Bremen, Germany

    Achim Gelessus

Authors
  1. Katja Windt
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  2. Till Becker
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  3. Oliver Jeken
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  4. Achim Gelessus
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Corresponding author

Correspondence to Till Becker.

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Windt, K., Becker, T., Jeken, O. et al. A classification pattern for autonomous control methods in logistics. Logist. Res. 2, 109–120 (2010). https://doi.org/10.1007/s12159-010-0030-9

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  • DOI: https://doi.org/10.1007/s12159-010-0030-9

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