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A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing

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Cited by:

  1. Dmitry Ivanov & Alexandre Dolgui, 2022. "Stress testing supply chains and creating viable ecosystems," Operations Management Research, Springer, vol. 15(1), pages 475-486, June.
  2. Issam Laguir & Sachin Modgil & Indranil Bose & Shivam Gupta & Rebecca Stekelorum, 2023. "Performance effects of analytics capability, disruption orientation, and resilience in the supply chain under environmental uncertainty," Annals of Operations Research, Springer, vol. 324(1), pages 1269-1293, May.
  3. Marco Bettiol & Mauro Capestro & Eleonora Di Maria & Roberto Ganau, 2024. "Is this time different? How Industry 4.0 affects firms’ labor productivity," Small Business Economics, Springer, vol. 62(4), pages 1449-1467, April.
  4. Shraddha Mishra & Surya Prakash Singh, 2022. "A stochastic disaster-resilient and sustainable reverse logistics model in big data environment," Annals of Operations Research, Springer, vol. 319(1), pages 853-884, December.
  5. Giuseppe Fragapane & Dmitry Ivanov & Mirco Peron & Fabio Sgarbossa & Jan Ola Strandhagen, 2022. "Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics," Annals of Operations Research, Springer, vol. 308(1), pages 125-143, January.
  6. Efpraxia D. Zamani & Conn Smyth & Samrat Gupta & Denis Dennehy, 2023. "Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review," Annals of Operations Research, Springer, vol. 327(2), pages 605-632, August.
  7. Brusset, Xavier & Ivanov, Dmitry & Jebali, Aida & La Torre, Davide & Repetto, Marco, 2023. "A dynamic approach to supply chain reconfiguration and ripple effect analysis in an epidemic," International Journal of Production Economics, Elsevier, vol. 263(C).
  8. Hanieh Shekarabi & Mohammad Mahdi Vali-Siar & Ashkan Mozdgir, 2024. "Food supply chain network design under uncertainty and pandemic disruption," Operational Research, Springer, vol. 24(2), pages 1-37, June.
  9. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
  10. Tüzün Tolga İnan & Neslihan Gökmen İnan, 2022. "The analysis of fatal aviation accidents more than 100 dead passengers: an application of machine learning," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1377-1395, December.
  11. Zhao, Nanyang & Hong, Jiangtao & Lau, Kwok Hung, 2023. "Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model," International Journal of Production Economics, Elsevier, vol. 259(C).
  12. Farheen Naz & Anil Kumar & Abhijit Majumdar & Rohit Agrawal, 2022. "Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research," Operations Management Research, Springer, vol. 15(1), pages 378-398, June.
  13. 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.
  14. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
  15. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
  16. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
  17. Timothy C. Y. Chan & Daniel Letourneau & Benjamin G. Potter, 2022. "Sparse flexible design: a machine learning approach," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 1066-1116, December.
  18. Lin, Sheng-Wei & Lu, Wen-Min, 2024. "Using inverse DEA and machine learning algorithms to evaluate and predict suppliers’ performance in the apple supply chain," International Journal of Production Economics, Elsevier, vol. 271(C).
  19. Yu, Yubing & Xu, Jiawei & Zhang, Justin Z. & Liu, Yulong (David) & Kamal, Muhammad Mustafa & Cao, Yanhong, 2024. "Unleashing the power of AI in manufacturing: Enhancing resilience and performance through cognitive insights, process automation, and cognitive engagement," International Journal of Production Economics, Elsevier, vol. 270(C).
  20. Ahmed Zainul Abideen & Veera Pandiyan Kaliani Sundram & Jaafar Pyeman & Abdul Kadir Othman & Shahryar Sorooshian, 2021. "Digital Twin Integrated Reinforced Learning in Supply Chain and Logistics," Logistics, MDPI, vol. 5(4), pages 1-22, November.
  21. Dou, Runliang & Liu, Xin & Hou, Yanchao & Wei, Yixin, 2024. "Mitigating closed-loop supply chain risk through assessment of production cost, disruption cost, and reliability," International Journal of Production Economics, Elsevier, vol. 270(C).
  22. Mahmoud Ashraf & Amr Eltawil & Islam Ali, 2024. "Disruption detection for a cognitive digital supply chain twin using hybrid deep learning," Operational Research, Springer, vol. 24(2), pages 1-31, June.
  23. Brylowski, Martin & Schröder, Meike & Lodemann, Sebastian & Kersten, Wolfgang, 2021. "Machine learning in supply chain management: A scoping review," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Ringle, Christian M. & Blecker, Thorsten (ed.), Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg Internationa, volume 31, pages 377-406, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
  24. Jian-Peng Chang & Heng-Xin Ren & Luis Martínez & Witold Pedrycz & Zhen-Song Chen, 2024. "Requirement-driven supplier selection: a multi-criteria QFD-based approach under epistemic and stochastic uncertainties," Annals of Operations Research, Springer, vol. 342(2), pages 1079-1128, November.
  25. Hu, Shaolong & Dong, Zhijie Sasha & Lev, Benjamin, 2022. "Supplier selection in disaster operations management: Review and research gap identification," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
  26. Simonetto, Marco & Sgarbossa, Fabio & Battini, Daria & Govindan, Kannan, 2022. "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda," International Journal of Production Economics, Elsevier, vol. 253(C).
  27. Meike Schroeder & Sebastian Lodemann, 2021. "A Systematic Investigation of the Integration of Machine Learning into Supply Chain Risk Management," Logistics, MDPI, vol. 5(3), pages 1-17, September.
  28. Guilherme Luz Tortorella & Anupama Prashar & Jiju Antony & Flavio S. Fogliatto & Vicente Gonzalez & Moacir Godinho Filho, 2024. "Industry 4.0 adoption for healthcare supply chain performance during COVID-19 pandemic in Brazil and India: the mediating role of resilience abilities development," Operations Management Research, Springer, vol. 17(2), pages 389-405, June.
  29. Chaima Ben Abdallah & Adnen El-Amraoui & François Delmotte & Ahmed Frikha, 2024. "A Hybrid Approach for Sustainable and Resilient Farmer Selection in Food Industry: Tunisian Case Study," Sustainability, MDPI, vol. 16(5), pages 1-30, February.
  30. Bernard Kamsu-Foguem & Philippe Clermont & Dieudonné Tchuente & Pierre Tiako & Samuel Fosso Wamba, 2023. "Service Provider Risk Mitigation in Aeronautics Supply Chains," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 615-631, December.
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