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A hybrid adaptive decision system for supply chain reconfiguration

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  • Navin K. Dev
  • Ravi Shankar
  • Angappa Gunasekaran
  • Lakshman S. Thakur

Abstract

Due to short product life cycle, it is expedient to reconfiguration an existing supply chain from time to time. Companies need to impose the standards on operational units for finding the best or the near best alternative configuration. Thus, it becomes imperative to effectively adapt various enablers in a supply chain by understanding the dynamics between them that help to reconfigure a supply chain for high levels of performance. This paper presents an integration of agent-based simulation and decision tree learning as the data mining techniques to determine adaptive decisions of operational units of a mobile phone supply chain. Agent-based simulation output is subjected to data mining analysis to understand system behaviour in terms of interactions and the factors influencing the performance. An entropy-based formulation is proposed as the basis for comparing different operational units in the supply chain. The insights obtained are then encapsulated as operational rules and guidelines supporting better decision-making.

Suggested Citation

  • Navin K. Dev & Ravi Shankar & Angappa Gunasekaran & Lakshman S. Thakur, 2016. "A hybrid adaptive decision system for supply chain reconfiguration," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7100-7114, December.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:23:p:7100-7114
    DOI: 10.1080/00207543.2015.1134842
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    References listed on IDEAS

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    Cited by:

    1. Naima Saeed & Kevin Cullinane & Victor Gekara & Prem Chhetri, 2021. "Reconfiguring maritime networks due to the Belt and Road Initiative: impact on bilateral trade flows," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(3), pages 381-400, September.
    2. Dev, Navin K. & Shankar, Ravi & Swami, Sanjeev, 2020. "Diffusion of green products in industry 4.0: Reverse logistics issues during design of inventory and production planning system," International Journal of Production Economics, Elsevier, vol. 223(C).
    3. Mohammad J. Aladaileh & Eva Lahuerta Otero, 2023. "The antecedents of SSCI: Evidence from the textile and fashion industry in Jordan," DOCFRADIS Working Papers 2302, Catedra Fundación Ramón Areces de Distribución Comercial, revised Mar 2023.
    4. Pournader, Mehrdokht & Ghaderi, Hadi & Hassanzadegan, Amir & Fahimnia, Behnam, 2021. "Artificial intelligence applications in supply chain management," International Journal of Production Economics, Elsevier, vol. 241(C).
    5. Lechtenberg, Sandra & Hellingrath, Bernd, 2021. "Applications of artificial intelligence in supply chain management: Identification of main research fields and greatest industry interests," ERCIS Working Papers 37, University of Münster, European Research Center for Information Systems (ERCIS).
    6. Anna Trunk & Hendrik Birkel & Evi Hartmann, 2020. "On the current state of combining human and artificial intelligence for strategic organizational decision making," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 875-919, November.
    7. Alba Barrero Caballero, 2023. "Comportamiento de consumo de los millennials y estrategias comunicativas en Facebook e Instagram del sector de la moda 2016-2019," DOCFRADIS Working Papers 2303, Catedra Fundación Ramón Areces de Distribución Comercial, revised Apr 2023.
    8. Devesh Kumar & Gunjan Soni & Rohit Joshi & Vipul Jain & Amrik Sohal, 2022. "Modelling supply chain viability during COVID-19 disruption: A case of an Indian automobile manufacturing supply chain," Operations Management Research, Springer, vol. 15(3), pages 1224-1240, December.
    9. Negar Jalilian & Seyed Mahmoud Zanjirchi & Alireza Naser Sadrabadi & Ahmadreza Asgharpourmasouleh & Mark Goh, 2021. "Agent-Based Approach to Configure Processes in Iran’s Banking Service Supply Chain," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    10. Lee, Neil Chueh-An, 2021. "Reconciling integration and reconfiguration management approaches in the supply chain," International Journal of Production Economics, Elsevier, vol. 242(C).

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