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Scheduling of recovery actions in the supply chain with resilience analysis considerations

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  • Dmitry Ivanov
  • Alexandre Dolgui
  • Boris Sokolov

Abstract

Supply chain engineering models with resilience considerations have been mostly focused on disruption impact quantification within one analysis layer, such as supply chain design or planning. Performance impact of disruptions has been typically analysed without scheduling of recovery actions. Taking into account schedule recovery actions and their duration times, this study extends the existing literature to supply chain scheduling and resilience analysis by an explicit integration of the optimal schedule recovery policy and supply chain resilience. In particular, we compute a schedule optimal control policy and analyse the performance of this policy by varying the perturbation vector and representing the outcomes of variations in the form of an attainable set. We propose a scheduling model that considers the coordination of recovery actions in the supply chain. Further, we suggest a resilience index by using the notion of attainable sets. The attainable sets are known in control theory; their calculation is based on the schedule control model results and the minimax regret approach for continuous time parameters given by intervals. We show that the proposed indicator can be used to estimate the impact of disruption and recovery dynamics on the achievement of planned performance in the supply chain.

Suggested Citation

  • Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov, 2018. "Scheduling of recovery actions in the supply chain with resilience analysis considerations," International Journal of Production Research, Taylor & Francis Journals, vol. 56(19), pages 6473-6490, October.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:19:p:6473-6490
    DOI: 10.1080/00207543.2017.1401747
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    Cited by:

    1. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    2. Sudip Adak & G. S. Mahapatra, 2021. "Effect of inspection and rework of probabilistic defective production on two-layer supply chain incorporating deterioration and reliability dependent demand," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 565-578, June.
    3. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    4. Jiakuan Chen & Haoyu Wen, 2023. "The application of complex network theory for resilience improvement of knowledge-intensive supply chains," Operations Management Research, Springer, vol. 16(3), pages 1140-1161, September.
    5. Kahr, Michael, 2022. "Determining locations and layouts for parcel lockers to support supply chain viability at the last mile," Omega, Elsevier, vol. 113(C).
    6. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2021. "The impact of congestion on protection decisions in supply networks under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    7. Fernando, Yudi & Bee, Poh Swan & Jabbour, Charbel Jose Chiappetta & Thomé, Antônio Márcio Tavares, 2018. "Understanding the effects of energy management practices on renewable energy supply chains: Implications for energy policy in emerging economies," Energy Policy, Elsevier, vol. 118(C), pages 418-428.

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