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A disruption recovery model for a single stage production-inventory system

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  • Hishamuddin, H.
  • Sarker, R.A.
  • Essam, D.

Abstract

This paper presents a newly developed disruption recovery model for a single stage production and inventory system, where the production is disrupted for a given period of time during the production up time. The model is categorized as a constrained non-linear optimization program which we have solved using an efficient heuristic developed in this paper. The model was also solved using an evolutionary algorithm and a comparison of the results from both methods was performed. The heuristic was able to accurately solve the model with significantly less time compared to the evolutionary algorithm. It can be shown that the optimal recovery schedule is dependent on the shortage cost parameters, as well as the extent of the disruption. The proposed model offers a potentially useful tool to help manufacturers decide on the optimal recovery plan in real time whenever the production system experiences a sudden disruption.

Suggested Citation

  • Hishamuddin, H. & Sarker, R.A. & Essam, D., 2012. "A disruption recovery model for a single stage production-inventory system," European Journal of Operational Research, Elsevier, vol. 222(3), pages 464-473.
  • Handle: RePEc:eee:ejores:v:222:y:2012:i:3:p:464-473
    DOI: 10.1016/j.ejor.2012.05.033
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    Cited by:

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    3. Sanjoy Kumar Paul & Sobhan Asian & Mark Goh & S. Ali Torabi, 2019. "Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss," Annals of Operations Research, Springer, vol. 273(1), pages 783-814, February.
    4. Paul, Sanjoy Kumar & Sarker, Ruhul & Essam, Daryl, 2014. "Real time disruption management for a two-stage batch production–inventory system with reliability considerations," European Journal of Operational Research, Elsevier, vol. 237(1), pages 113-128.
    5. Shao, Xiao-Feng, 2018. "Production disruption, compensation, and transshipment policies," Omega, Elsevier, vol. 74(C), pages 37-49.
    6. Chen, Li-Ming & Chang, Wei-Lun, 2021. "Supply- and cyber-related disruptions in cloud supply chain firms: Determining the best recovery speeds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    7. Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam, 2018. "A reactive mitigation approach for managing supply disruption in a three-tier supply chain," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1581-1597, October.
    8. Azad, Nader & Hassini, Elkafi, 2019. "Recovery strategies from major supply disruptions in single and multiple sourcing networks," European Journal of Operational Research, Elsevier, vol. 275(2), pages 481-501.
    9. Hishamuddin, Hawa & Sarker, Ruhul A. & Essam, Daryl, 2014. "A recovery mechanism for a two echelon supply chain system under supply disruption," Economic Modelling, Elsevier, vol. 38(C), pages 555-563.
    10. Zhu, Xiaoyan & Cao, Yunzhi, 2021. "The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    11. Paul, Sanjoy Kumar & Sarker, Ruhul & Essam, Daryl, 2014. "Managing real-time demand fluctuation under a supplier–retailer coordinated system," International Journal of Production Economics, Elsevier, vol. 158(C), pages 231-243.
    12. Na Wang & Jingze Chen & Hongfeng Wang, 2023. "Resilient Supply Chain Optimization Considering Alternative Supplier Selection and Temporary Distribution Center Location," Mathematics, MDPI, vol. 11(18), pages 1-22, September.
    13. A. Thangam, 2017. "Retailer’s optimal replenishment policy in a two-echelon supply chain under two-part delay in payments and disruption in delivery," 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. 8(1), pages 26-46, January.
    14. Sarker, Ruhul & Essam, Daryl, 2017. "A quantitative model for disruption mitigation in a supply chainAuthor-Name: Paul, Sanjoy Kumar," European Journal of Operational Research, Elsevier, vol. 257(3), pages 881-895.
    15. Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam & Paul Tae-Woo Lee, 2019. "A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain," Annals of Operations Research, Springer, vol. 280(1), pages 299-335, September.
    16. Bao, Xing & Diabat, Ali & Zheng, Zhongliang, 2020. "An ambiguous manager's disruption decisions with insufficient data in recovery phase," International Journal of Production Economics, Elsevier, vol. 221(C).

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