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Multi-agent System for Simulation of Response to Supply Chain Disruptions

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Intelligent Distributed Computing XIII (IDC 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 868))

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Abstract

Global supply networks of manufacturing companies face many types of disruption. Quick decision-making with only limited information is often required. We propose a novel agent-based planning and scheduling simulation system, which can make rescheduling suggestions within minutes and with limited change to the existing plan. By simulating disruptions of various nature and severity in advance, the system also serves to support preventive supply chain design changes.

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Author information

Authors and Affiliations

  1. Huawei Technologies Co. Ltd., Bantian, Longgang District, Shenzhen, 518129, China

    Jing Tan, Rongjun Xu & Kai Chen

  2. City University of Applied Sciences Bremen, Neustadtswall 30, 28199, Bremen, Germany

    Lars Braubach

  3. Brandenburg University of Applied Sciences, Magdeburger Str. 50, 14770, Brandenburg, Germany

    Kai Jander

  4. Actoron GmbH, Richardstr. 49, 22081, Hamburg, Germany

    Alexander Pokahr

Authors
  1. Jing Tan
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  2. Rongjun Xu
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  3. Kai Chen
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  4. Lars Braubach
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  5. Kai Jander
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  6. Alexander Pokahr
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Corresponding authors

Correspondence to Jing Tan , Rongjun Xu , Kai Chen , Lars Braubach , Kai Jander or Alexander Pokahr .

Editor information

Editors and Affiliations

  1. SPIIRAS, St. Petersburg, Russia

    Igor Kotenko

  2. University of Craiova, Craiova, Romania

    Costin Badica

  3. SPIIRAS, St. Petersburg, Russia

    Vasily Desnitsky

  4. LAAS - CNRS, Toulouse Cedex 4, France

    Didier El Baz

  5. University of Novi Sad, Novi Sad, Serbia

    Mirjana Ivanovic

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Tan, J., Xu, R., Chen, K., Braubach, L., Jander, K., Pokahr, A. (2020). Multi-agent System for Simulation of Response to Supply Chain Disruptions. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_15

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