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An autonomous multi-agent approach to supply chain event management

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  • Bearzotti, Lorena A.
  • Salomone, Enrique
  • Chiotti, Omar J.

Abstract

Organizations have made a significant effort to implement software for planning and scheduling, but disruptive event management is still a problem to be solved. Since a disruptive event can affect the overall performance of the supply chain, SCEM (Supply Chain Event Management) systems presenting different automation levels such as monitoring, alarm and decision support have been proposed. However, the management of disruptive events, taking into account the distributed nature of the supply chain, the members' autonomy and the ability to exert corrective control actions, has been identified as a problem that requires further research. This work presents an agent-based approach for the SCEM problem, which can perform autonomous corrective control actions to minimize the effect of deviations in the plan that is currently being executed. These control actions consist of a distribution of the variation between supply chain members, using the plan's slack in a collaborative way. An innovative feature of this approach is its focus on resources, which are affected by disruptive events in a direct way. Based on this approach, a SCEM system is designed as a net of control points defined on resources connected through supply process orders. Two novel aspects are the distributed collaborative inter-organizational architecture of the SCEM system and a Double Contract Net Protocol. This protocol allows a set of resource:representing agents to interact through an agent, representing a supply process order as a mediator. An application to a case study of the Multi-Agent SCEM system implemented with JADE is provided.

Suggested Citation

  • Bearzotti, Lorena A. & Salomone, Enrique & Chiotti, Omar J., 2012. "An autonomous multi-agent approach to supply chain event management," International Journal of Production Economics, Elsevier, vol. 135(1), pages 468-478.
    • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:468-478
    DOI: 10.1016/j.ijpe.2011.08.023
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    References listed on IDEAS

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    1. Trkman, Peter & McCormack, Kevin, 2009. "Supply chain risk in turbulent environments--A conceptual model for managing supply chain network risk," International Journal of Production Economics, Elsevier, vol. 119(2), pages 247-258, June.
    2. Cauvin, A.C.A. & Ferrarini, A.F.A. & Tranvouez, E.T.E., 2009. "Disruption management in distributed enterprises: A multi-agent modelling and simulation of cooperative recovery behaviours," International Journal of Production Economics, Elsevier, vol. 122(1), pages 429-439, November.
    3. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    4. Oke, Adegoke & Gopalakrishnan, Mohan, 2009. "Managing disruptions in supply chains: A case study of a retail supply chain," International Journal of Production Economics, Elsevier, vol. 118(1), pages 168-174, March.
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    Cited by:

    1. Bearzotti, Lorena & Gonzalez, Rosa, 2014. "A Multi-Agent Based Approach for Risk Management in a Port Container Terminal," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Next Generation Supply Chains: Trends and Opportunities. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 18, volume 18, pages 515-530, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. H. Norouzi Nav & M. R. Jahed Motlagh & A. Makui, 2017. "Robust controlling of chaotic behavior in supply chain networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 711-724, June.
    3. Adhau, Sunil & Mittal, M.L. & Mittal, Abhinav, 2013. "A multi-agent system for decentralized multi-project scheduling with resource transfers," International Journal of Production Economics, Elsevier, vol. 146(2), pages 646-661.
    4. Kucukkoc, Ibrahim & Zhang, David Z., 2014. "Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines," International Journal of Production Economics, Elsevier, vol. 158(C), pages 314-333.
    5. Ra¡¯ed Masa¡¯deh & Ali Al-Badi & Aseel Rashaideh & Jaafer Abu-Zahra & Jamal Alsmadi, 2017. "Factors Influencing Continuous Intention to Use of Event Management Electronic Portals in 4 and 5 Star Hotels," Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 8(3), pages 1-19, June.
    6. Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), 2014. "Next Generation Supply Chains: Trends and Opportunities," Proceedings of the Hamburg International Conference of Logistics (HICL), Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management, volume 18, number 18.
    7. Xu, Liming & Mak, Stephen & Brintrup, Alexandra, 2021. "Will bots take over the supply chain? Revisiting agent-based supply chain automation," International Journal of Production Economics, Elsevier, vol. 241(C).

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