Reliable Supply Chain Network Design Considering Resilience Strategies Under Risk of Disruption

Document Type : Research Paper


1 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran



This paper presents a scenario-based supply chain network design (SCND) model in the case of disruption occurrence with a single product type. The proposed supply chain (SC) comprises three echelons, including manufacturers, distribution centers (DCs), and customers. Two kinds of DCs, namely reliable and unreliable DCs, are considered in the presented model. Disruption affects unreliable DCs and causes the loss of a portion of their capacity. Thus, an unreliable DC capacity in each period is assumed to be a positive variable specified based on its capacity in the previous period. There are different investment levels for establishing each DC, which affects the amount of capacity loss due to disruption. Two resilience strategies, DC capacity fortification and inventory keeping are considered to reduce the effects of disruption on SC, and the results under each strategy are investigated. The outcomes are investigated by presenting numerical examples, and the advantages of the proactive manner versus reactive manner are shown. Finally, sensitivity analysis is done on disruption related parameters to show how parameters influence the model outputs.


Azad, N., Davoudpour, H., Saharidis, G. K., & Shiripour, M. (2014). A new model to mitigating random disruption risks of facility and transportation in supply chain network design. The International Journal of Advanced Manufacturing Technology, 70(9-12), 1757-1774.
Barroso, A., Machado, V. C., & Machado, V. (2011). Supply chain resilience using the mapping approach: INTECH Open Access Publisher.
Bode, C., & Wagner, S. M. (2015). Structural drivers of upstream supply chain complexity and the frequency of supply chain disruptions. Journal of Operations Management, 36, 215-228.
Boone, C. A., Craighead, C. W., Hanna, J. B., & Nair, A. (2013). Implementation of a system approach for enhanced supply chain continuity and resiliency: A longitudinal study. Journal of Business Logistics, 34(3), 222-235.
Cardona-Valdés, Y., Álvarez, A., & Ozdemir, D. (2011). A bi-objective supply chain design problem with uncertainty. Transportation Research Part C: Emerging Technologies, 19(5), 821-832.
Carvalho, H., Azevedo, S. G., & Cruz-Machado, V. (2012). Agile and resilient approaches to supply chain management: influence on performance and competitiveness. Logistics research, 4(1-2), 49-62.
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.
Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The international journal of logistics management, 15(2), 1-14.
Diabat, A., Govindan, K., & Panicker, V. V. (2012). Supply chain risk management and its mitigation in a food industry. International Journal of Production Research, 50(11), 3039-3050.
Drezner, Z. (1987). Heuristic solution methods for two location problems with unreliable facilities. Journal of the Operational Research Society, 38(6), 509-514.
Erol, O., Sauser, B. J., & Mansouri, M. (2010). A framework for investigation into extended enterprise resilience. Enterprise Information Systems, 4(2), 111-136.
Elluru, S., Gupta, H., Kaur, H., & Singh, S. P. (2019). Proactive and reactive models for disaster resilient supply chain. Annals of Operations Research283(1-2), 199-224.
Farrokhi-Asl, H., Makui, A., Ghousi, R., & Rabbani, M. (2020). Developing a hazardous waste management system with consideration of health, safety, and environment. Computers & Electrical Engineering82, 106553.
Giri, B. C., & Bardhan, S. (2015). Coordinating a supply chain under uncertain demand and random yield in presence of supply disruption. International Journal of Production Research, 53(16), 5070-5084.
Gholami, F., Paydar, M. M., Hajiaghaei-Keshteli, M., & Cheraghalipour, A. (2019). A multi-objective robust supply chain design considering reliability. Journal of Industrial and Production Engineering36(6), 385-400.
Ghomi, S. F., & Asgarian, B. (2019). Development of metaheuristics to solve a transportation inventory location routing problem considering lost sale for perishable goods. Journal of Modelling in Management, 14(1), 175-198.
Hasani, A., & Zegordi, S. H. (2015). A robust competitive global supply chain network design under disruption: the case of medical device industry. International Journal of Industrial Engineering & Production Research26(1), 63-84.
Hasani, A., & Khosrojerdi, A. (2016). Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study. Transportation Research Part E: Logistics and Transportation Review, 87, 20-52.
Hosseini, S., Ivanov, D., & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation Research Part E: Logistics and Transportation Review125, 285-307.
Jabbarzadeh, A., Jalali Naini, S. G., Davoudpour, H., & Azad, N. (2012). Designing a supply chain network under the risk of disruptions. Mathematical Problems in Engineering, 2012.
Mensah, P., & Merkuryev, Y. (2014). Developing a resilient supply chain. Procedia-Social and Behavioral Sciences, 110, 309-319.
Moradi, A., Razmi, J., Babazadeh, R., & Sabbaghnia, A. (2019). An integrated principal component analysis and multi-objective mathematical programming approach to agile supply chain network design under uncertainty. Journal of Industrial & Management Optimization15(2), 855.
Peng, P., Snyder, L. V., Lim, A., & Liu, Z. (2011). Reliable logistics networks design with facility disruptions. Transportation Research Part B: Methodological, 45(8), 1190-1211.
Pettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring supply chain resilience: development and implementation of an assessment tool. Journal of Business Logistics, 34(1), 46-76.
Ponis, S. T., & Koronis, E. (2012). Supply chain resilience: definition of concept and its formative elements. Journal of Applied Business Research, 28(5), 921.
Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124-143.
Qiu, R., & Wang, Y. (2016). Supply chain network design under demand uncertainty and supply disruptions: a distributionally robust optimization approach. Scientific Programming2016, 1-15.
Rabbani, M., Hosseini-Mokhallesun, S. A. A., Ordibazar, A. H., & Farrokhi-Asl, H. (2020). A hybrid robust possibilistic approach for a sustainable supply chain location-allocation network design. International Journal of Systems Science: Operations & Logistics7(1), 60-75.
Ribeiro, J. P., & Barbosa-Povoa, A. (2018). Supply Chain Resilience: Definitions and quantitative modelling approaches–A literature review. Computers & Industrial Engineering115, 109-122.
Sabouhi, F., Pishvaee, M. S., & Jabalameli, M. S. (2018). Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain. Computers & Industrial Engineering126, 657-672.
Sadghiani, N. S., Torabi, S., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 75, 95-114.
Sáenz, M. J., & Revilla, E. (2014). Creating more resilient supply chains. MIT Sloan management review, 55(4), 22.
Scholten, K., Sharkey Scott, P., & Fynes, B. (2014). Mitigation processes–antecedents for building supply chain resilience. Supply Chain Management: An International Journal, 19(2), 211-228.
Sherali, H. D., & Adams, W. P. (2013). A reformulation-linearization technique for solving discrete and continuous nonconvex problems (Vol. 31): Springer Science & Business Media.
Silva, N., Ferreira, L. M. D., Silva, C., Magalhães, V., & Neto, P. (2017). Improving supply chain visibility with artificial neural networks. Procedia Manufacturing11, 2083-2090.
Simchi-Levi, D., Wang, H., & Wei, Y. (2013). Increasing supply chain robustness through process flexibility and strategic inventory. Operations Research.
Snyder, L. V., & Daskin, M. S. (2005). Reliability models for facility location: the expected failure cost case. Transportation Science, 39(3), 400-416.
Tang, C. S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103(2), 451-488.
Torabi, S., Baghersad, M., & Mansouri, S. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22-48.
Wieland, A., & Wallenburg, C. M. (2013). The influence of relational competencies on supply chain resilience: a relational view. International journal of physical distribution & logistics management, 43(4), 300-320.
Xu, M., Wang, X., & Zhao, L. (2014). Predicted supply chain resilience based on structural evolution against random supply disruptions. International Journal of Systems Science: Operations & Logistics, 1(2), 105-117.