Designing a Model for Intertwined Supply Network Based on Resilience

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran

2 Professor, Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran

3 Assistant Professor, Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran

Abstract

Recently, supply chains and supply networks are developing towards intertwined supply networks. These new, dynamic structures are different from linear supply chains with static structures and require a revision of some traditional concepts. The aim of this research is mathematical modeling of the three-level supply network (including suppliers, firms, customers) based on resilience. Its approach is quantitative and mathematical modeling. In this research, first the problem is modeled and solved using real data in GAMS software, and after determining the optimal values ​​of the decision variables, the results are analyzed. Also, a sensitivity analysis has been performed on the effective parameter (production capacity). The analysis of the results showed that increase of the capacity parameter did not affect the total cost of the network due to the constant demand. The proposed model, while optimizing the intertwined supply networks, is able to strengthen the resilience of the network in the face of disruption. On the other hand, the effectiveness of the proposed approach has been shown by using it in a case study of the intertwined supply network of tiles and ceramics.

Keywords

References

  • Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. International Journal of Production Research, 58(10), 2904-2915.
  • Feizabadi, J., Gligor, D. M., & Choi, T. Y. (2021). Examining the resiliency of intertwined supply networks: a jury-rigging perspective. International Journal of Production Research, 1-20.
  • Wang, M., & Yao, J. (2021). Intertwined supply network design under facility and transportation disruption from the viability perspective. International Journal of Production Research, 1-31.
  • Levalle, R. R., & Nof, S. Y. (2015). Resilience by teaming in supply network formation and re-configuration. International Journal of Production Economics, 160, 80-93.
  • Ivanov, D. (2020). Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic. Annals of Operations Research, 1-21.
  • Fraccascia, L., Giannoccaro, I., & Albino, V. (2017). Rethinking resilience in industrial symbiosis: conceptualization and measurements. Ecological Economics, 137, 148-162.
  • Dubey, R., A. Gunasekaran, and T. Papadopoulos. (2019b). “Disaster Relief Operations: Past, Present and Future.” Annals of Operations Research 283 (1-2): 1–8.
  • Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829-846.
  • Ivanov, D., & Dolgui, A. (2019). Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience. International Journal of Production Research, 57(15-16), 5119-5136.
  • Chibani, A., Delorme, X., Dolgui, A., & Pierreval, H. (2018). Dynamic optimisation for highly agile supply chains in e-procurement context. International journal of production research, 56(17), 5904-5929.
  • Wang, J., R. Dou, R. R. Muddada, and W. Zhang. (2018). “Management of a Holistic Supply Chain Network for Proactive Resilience: Theory and Case Study.” Computers and Industrial Engineering 125: 668–677.
  • Kelly, K., and K. Marchese. (2015). Supply Chains and ISNs. Business Ecosystems Come of age. Deloitte University Press, pp. 55–65.
  • Demirel, G., MacCarthy, B. L., Ritterskamp, D., Champneys, A. R., & Gross, T. (2019). Identifying dynamical instabilities in supply networks using generalized modeling. Journal of Operations Management, 65(2), 136-159.
  • Zhao, K., Zuo, Z., & Blackhurst, J. V. (2019). Modelling supply chain adaptation for disruptions: An empirically grounded complex adaptive systems approach. Journal of Operations Management, 65(2), 190-212.
  • Pavlov, A., Ivanov, D., Pavlov, D., & Slinko, A. (2019b). Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics. Annals of Operations Research, 1-30.
  • Tan, W. J., Cai, W., & Zhang, A. N. (2020). Structural-aware simulation analysis of supply chain resilience. International Journal of Production Research, 58(17), 5175-5195.
  • Dubey, R., Gunasekaran, A., Childe, S. J., Fosso Wamba, S., Roubaud, D., & Foropon, C. (2021). Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research, 59(1), 110-128.
  • خلیلی، پویا، کاظمی، فکور، ثقیه، امیرمحمد. (1401). طراحی یک شبکه زنجیره‌تأمین بنزین پایدار و تاب‌آور تحت شرایط عدم قطعیت اختلال (مطالعه موردی: شبکه زنجیره‌تأمین بنزین استان خراسان رضوی). مدیریت صنعتی، 14(1)، 27-79.‎
  • موسوی، مهسا، جمالی، غلامرضا، قربانپور، احمد. (1400). ارائه مدل بهینه‌سازی شبکه‎ زنجیره‌تأمین سبزـتاب‌آور در صنایع سیمان. مدیریت صنعتی، 13(2)، 222-245.
  • شیشه بری، داوود، عبدالعظیمی، امید، عندلیب اردکانی، داوود. (1400). زنجیره‌تأمین حلقه بسته پایدار و تاب‌آور دارو با تأمین‌کننده پشتیبان تحت شرایط بیماری کرونا (کووید-19). نشریه پژوهش‌های مهندسی صنایع در سیستم‌های تولید، 9(19)، 33-53.
  • Mousazadeh, M., Torabi, S. A., & Zahiri, B. (2015). A robust possibilistic programming approach for pharmaceutical supply chain network design. Computers & Chemical Engineering, 82, 115-128.
  • Balaman, Ş. Y., & Selim, H. (2016). Sustainable design of renewable energy supply chains integrated with district heating systems: A fuzzy optimization approach. Journal of cleaner production, 133, 863-885.
  • Cardoso, S. R., Barbosa-Póvoa, A. P., Relvas, S., & Novais, A. Q. (2015). Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega, 56, 53-73.
  • Carvalho, H., Barroso, A. P., Machado, V. H., Azevedo, S., & Cruz-Machado, V. (2012). Supply chain redesign for resilience using simulation. Computers & Industrial Engineering, 62(1), 329-341.
  • Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22-48.
  • Fahimnia, B., & Jabbarzadeh, A. (2016). Marrying supply chain sustainability and resilience: A match made in heaven. Transportation Research Part E: Logistics and Transportation Review, 91, 306-324.
  • Zahiri, B., Zhuang, J., & Mohammadi, M. (2017). Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study. Transportation Research Part E: Logistics and Transportation Review, 103, 109-142.
  • زمانیان، محمدرضا. (1399). مدل‌سازی ریاضی زنجیره‌تأمین تاب‌آور و پایدار نفت و گاز طبیعی (چاپ اول). نشر اسماء الزهرا.

Tsao, Y. C., Thanh, V. V., Lu, J. C., & Wei, H. H. (2021). A risk-sharing-based resilient renewable energy supply network model under the COVID-19 pandemic. Sustainable Production and Consumption, 25, 484-498.

Journal of Industrial Engineering Research in Production Systems
Volume 10, Issue 20
January 0
Pages 77-89

Files

Share

How to cite

Statistics