• DocumentCode
    1793177
  • Title

    Multi-agent models to study the robustness and resilience of complex supply chain networks

  • Author

    Ponnambalam, Loganathan ; Do Huynh Long ; Sarawgi, Disha ; Xiuju Fu ; Goh, Rick Siow Mong

  • Author_Institution
    Comput. Sci., Inst. of High Performance Comput., A*STAR, Singapore, Singapore
  • fYear
    2014
  • fDate
    19-21 Aug. 2014
  • Firstpage
    7
  • Lastpage
    12
  • Abstract
    Increase in the rate of disruptive events in the recent times and their economic implications on business continuity have raised the attention in supply chain disruption research. Effective strategic planning during disruptions can be accomplished by assessing the robustness and resilience of the existing supply chain network. This talk will illustrate the application of multi-agent approach at modeling supply chain network as complex adaptive systems and investigating the supply chain network´s structural characteristics via social network analysis. The proposed approach provides a better opportunity to achieve our objective - to understand the emergence of complex supply chain networks, assess the network vulnerability after its emergence and study the robustness, resilience of the network to hypothetical internal/external disruptive scenarios. Also, the intelligence of the associated entities, their decision making´s influence on the network´s emergance, its productivity and its structural characteristics at the network level will be addressed. Supply chain disruption management researchers can use the proposed approach to evaluate the robustness of their network and assess its resilience for varying degrees of disruptions.
  • Keywords
    business continuity; multi-agent systems; social networking (online); strategic planning; supply chain management; business continuity; complex adaptive system; complex supply chain network; disruptive event; multiagent model; social network analysis; strategic planning; supply chain disruption management; supply chain disruption research; supply chain network structural characteristic; Measurement; Quality of service; Resilience; Robustness; Social network services; Supply chains; Business Continuity; complex supply chain networks; disruptions; multi-agent modeling; resilience; robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Autonomous Agents, Networks and Systems (INAGENTSYS), 2014 IEEE International Conference on
  • Conference_Location
    Bandung
  • Print_ISBN
    978-1-4799-4803-1
  • Type

    conf

  • DOI
    10.1109/INAGENTSYS.2014.7005717
  • Filename
    7005717