Statistics
| Number of Journals | 22 |
| Number of Issues | 485 |
| Number of Articles | 5,052 |
| Article View | 9,296,989 |
| PDF Download | 6,139,830 |
Resilient Mixed Supply Chain Network Redesign Under Operational And Disruption Risks: A Case Study | ||
| نشریه پژوهش های مهندسی صنایع در سیستم های تولید | ||
| Volume 8, Issue 16, September 2020, Pages 113-135 PDF (1.32 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.22084/ier.2020.20467.1915 | ||
| Authors | ||
| Mohammad Mahdi Vali-Siar1; Emad Roghanian* 2 | ||
| 1phD candidate, Department of industrial engineering, K.N. Toosi university of technology | ||
| 2Associate professor, Department of industrial engineering, K.N. Toosi university of technology | ||
| Abstract | ||
| Today, supply chains are exposed to a variety of risks. Ignoring these risks can cause irreparable damage to them. On the other hand, the subject of redesigning is essential when the supply chain loses its optimality or needs to be altered due to changing conditions. In this paper, in contrast to most researches done in the literature, the problem of resilient supply chain network redesign is investigated under operational and disruption risks. The network structure addressed in this paper is a mixture of open and closed loop schemes, which has been rarely considered in the literature. A novel stochastic robust optimization model is developed to manage the uncertainty of the problem. The problem is formulated as a linear mixed-integer programming model with the objective function of profit maximization. Due to the high complexity of the model and the challenge to solve it in large-scale dimensions, a Lagrangian relaxation algorithm is developed, and its excellent performance is shown by the relevant calculations. In order to measure the efficiency and validity of the model, a case study has been presented in the automotive tire industry. The results show that using resilience strategies is very effective in improving the profitability of the supply chain and preventing losses. In addition, the use of a mixed supply chain network increases the overall profitability of the supply chain in comparison to a forward supply chain network. | ||
| Keywords | ||
| Supply chain network design; Resilience; Operational and disruption risks; Stochastic programming; Mixed open and closed loop supply chain | ||
| References | ||
|
[1] Govindan, K., Fattahi, M., Keyvanshokooh, E. (2017). “Supply chain network design under uncertainty: A comprehensive review and future research directions”, European Journal of Operational Research, 263(1): 108-141.
[2] Zokaee, S., Jabbarzadeh, A., Fahimnia, B., Sadjadi, S. J. (2017). “Robust supply chain network design: an optimization model with real world application”, Annals of Operations Research, 257(1-2): 15-44.
[3] Jabbarzadeh, A., Fahimnia, B., Sheu, J. B., Moghadam, H. S. (2016). “Designing a supply chain resilient to major disruptions and supply/demand interruptions”, Transportation Research Part B: Methodological, 94: 121-149.
[4] Tang, C. S. (2006). “Perspectives in supply chain risk management”, International journal of production economics, 103(2): 451-488.
[5] Singh, A. R., Mishra, P. K., Jain, R., Khurana, M. K. (2012). “Design of global supply chain network with operational risks”, The International Journal of Advanced Manufacturing Technology, 60(1-4): 273-290.
[6] Sheffi, Y. (2005). The resilient enterprise: overcoming vulnerability for competitive advantage, 1st Edition MIT Press.
[7] Torabi, S. A., Namdar, J., Hatefi, S. M., Jolai, F. (2016). “An enhanced possibilistic programming approach for reliable closed-loop supply chain network design”, International Journal of Production Research, 54(5): 1358-1387.
[8] 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 Engineering, 126: 657-672.
[9] Tang, C. S. (2006). “Robust strategies for mitigating supply chain disruptions”, International Journal of Logistics: Research and Applications, 9(1): 33-45.
[10] Diabat, A., Dehghani, E., Jabbarzadeh, A. (2017). “Incorporating location and inventory decisions into a supply chain design problem with uncertain demands and lead times”, Journal of Manufacturing Systems, 43: 139-149.
[11] Kristianto, Y., Gunasekaran, A., Helo, P., Hao, Y. (2014). “A model of resilient supply chain network design: A two-stage programming with fuzzy shortest path”, Expert systems with applications, 41(1): 39-49.
[12] Petersen, K. J., Handfield, R. B., Ragatz, G. L. (2005). “Supplier integration into new product development: coordinating product, process and supply chain design”, Journal of operations management, 23(3-4): 371-388.
[13] Khatami, M., Mahootchi, M., Farahani, R. Z. (2015). “Benders’ decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties”, Transportation Research Part E: Logistics and Transportation Review, 79: 1-21.
[14] Jahani, H., Abbasi, B., Alavifard, F., Talluri, S. (2018). “Supply chain network redesign with demand and price uncertainty”, International Journal of Production Economics, 205: 287-312.
[15] Akçalı, E., Çetinkaya, S., Üster, H. (2009). “Network design for reverse and closed‐loop supply chains: An annotated bibliography of models and solution approaches”, Networks, 53(3): 231-248.
[16] Soleimani, H., Kannan, G. (2015). “A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks”, Applied Mathematical Modelling, 39(14): 3990-4012.
]17[ حسنی، علیاکبر، حسینی، سید محمدحسن (1395). "ارائه یک مدل استوار چندهدفه برای طراحی شبکه زنجیرهتأمین برگشتی با قیمتگذاری پویا تحت عدمقطعیت و بهکارگیری الگوریتم جستجوی ممتیک با پردازش موازی"، نشریه پژوهشهای مهندسی صنایع در سیستمهای تولید، 4(7): 17-35. [18] Van Engeland, J., Beliën, J., De Boeck, L., De Jaeger, S. (2018). Literature review: strategic network optimization models in waste reverse supply chains, Omega: Article in press.
[19] Govindan, K., Soleimani, H., Kannan, D. (2015). “Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future”, European journal of operational research, 240(3): 603-626.
[20] Gou, Q., Liang, L., Huang, Z., Xu, C. (2008). “A joint inventory model for an open-loop reverse supply chain”, International Journal of Production Economics, 116(1): 28-42.
[21] Salema, M. I. G., Barbosa-Povoa, A. P., Novais, A. Q. (2007). “An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty”, European journal of operational research, 179(3): 1063-1077.
[22] Özceylan, E. (2016). “Simultaneous optimization of closed-and open-loop supply chain networks with common components”, Journal of Manufacturing Systems, 41: 143-156.
[23] Melo, M. T., Nickel, S., Saldanha-da-Gama, F. (2012). “A tabu search heuristic for redesigning a multi-echelon supply chain network over a planning horizon”, International Journal of Production Economics, 136(1): 218-230.
[24] Fattahi, M., Govindan, K., Keyvanshokooh, E. (2018). “A multi-stage stochastic program for supply chain network redesign problem with price-dependent uncertain demands”, Computers & Operations Research, 100: 314-332.
[25] Bing, X., Bloemhof-Ruwaard, J., Chaabane, A., van der Vorst, J. (2015). “Global reverse supply chain redesign for household plastic waste under the emission trading scheme”, Journal of cleaner production, 103: 28-39.
[26] Feitó-Cespón, M., Sarache, W., Piedra-Jimenez, F., Cespón-Castro, R. (2017). “Redesign of a sustainable reverse supply chain under uncertainty: A case study”, Journal of Cleaner Production, 151: 206-217.
[27] 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
[28] Azad, N., Saharidis, G. K., Davoudpour, H., Malekly, H., Yektamaram, S. A. (2013). “Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach”, Annals of Operations Research, 210(1): 125-163.
[29] Rezapour, S., Farahani, R. Z., Pourakbar, M. (2017). “Resilient supply chain network design under competition: a case study”, European Journal of Operational Research, 259(3): 1017-1035.
[30] Sadghiani, N. S., Torabi, S. A., Sahebjamnia, N. (2015). “Retail supply chain network design under operational and disruption risks”, Transportation Research Part E: Logistics and Transportation Review, 75: 95-114.
[31] Nooraie, S. V., Parast, M. M. (2016). “Mitigating supply chain disruptions through the assessment of trade-offs among risks, costs and investments in capabilities”, International Journal of Production Economics, 171: 8-21.
[32] 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.
[33] Dehghani, E., Jabalameli, M. S., Jabbarzadeh, A., Pishvaee, M. S. (2018). “Resilient solar photovoltaic supply chain network design under business-as-usual and hazard uncertainties”, Computers & Chemical Engineering, 111: 288-310.
[34] Fattahi, M., Govindan, K., Keyvanshokooh, E. (2017). “Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers”, Transportation Research Part E: Logistics and Transportation Review, 101: 176-200.
[35] Behzadi, G., O'Sullivan, M. J., Olsen, T. L., Scrimgeour, F., Zhang, A. (2017). “Robust and resilient strategies for managing supply disruptions in an agribusiness supply chain”, International Journal of Production Economics, 191, 207-220.
[36] Ghavamifar, A., Makui, A., Taleizadeh, A. A. (2018). “Designing a resilient competitive supply chain network under disruption risks: A real-world application”, Transportation Research Part E: Logistics and Transportation Review, 115: 87-109.
[37] Bottani, E., Murino, T., Schiavo, M., Akkerman, R. (2019). “Resilient food supply chain design: Modelling framework and metaheuristic solution approach”, Computers & Industrial Engineering, 135: 177-198.
[38] Jabbarzadeh, A., Haughton, M., Khosrojerdi, A. (2018). “Closed-loop supply chain network design under disruption risks: A robust approach with real world application”, Computers & Industrial Engineering, 116: 178-191.
]39[ علیخانی، رضا، ترابی، سید علی. (1397). "بازطراحی شبکههای زنجیرهتأمین خردهفروشی براساس قابلیتهای چندگانه بازگشتپذیری"، نشریه پژوهشهای نوین در تصمیمگیری، 3(4): 73-102 [40] Fattahi, M., Govindan, K., Maihami, R. (2020). “Stochastic optimization of disruption-driven supply chain network design with a new resilience metric”, International Journal of Production Economics: Article in press, Vol 230: 107755. https://doi.org/10.1016/j.ijpe.2020.107755.
[41] Haeri, A., Hosseini‐Motlagh, S. M., Ghatreh Samani, M. R., Rezaei, M. (2020). “A mixed resilient‐efficient approach toward blood supply chain network design”, International Transactions in Operational Research, 27(4): 1962-2001.
[42] Tucker, E. L., Daskin, M. S., Sweet, B. V., Hopp, W. J. (2020). “Incentivizing resilient supply chain design to prevent drug shortages: policy analysis using two-and multi-stage stochastic programs”. IISE Transactions, 52(4): 394-412.
[43] Masoudipour, E., Amirian, H., Sahraeian, R. (2017). “A novel closed-loop supply chain based on the quality of returned product”, Journal of cleaner production, 151: 344-355.
[44] Sahebjamnia, N., Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M. (2018). “Sustainable tire closed-loop supply chain network design: Hybrid metaheuristic algorithms for large-scale networks”, Journal of cleaner production, 196: 273-29.
[45] Gabrel, V., Murat, C., Thiele, A. (2014). “Recent advances in robust optimization: An overview”, European journal of operational research, 235(3): 471-483.
[46] Gorissen, B. L., Yanıkoğlu, İ., den Hertog, D. (2015). “A practical guide to robust optimization”, Omega, 53: 124-137.
[47] Bertsimas, D., Brown, D. B., Caramanis, C. (2011). “Theory and applications of robust optimization”, SIAM review, 53(3): 464-501.
[48] Mulvey, J. M., Vanderbei, R. J., Zenios, S. A. (1995). “Robust optimization of large-scale systems”, Operations research, 43(2): 264-281.
[49] Jabbarzadeh, A., Fahimnia, B., Seuring, S. (2014). “Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application”. Transportation Research Part E: Logistics and Transportation Review, 70, 225-244.
[50] Aghezzaf, E. H., Sitompul, C., Najid, N. M. (2010). “Models for robust tactical planning in multi-stage production systems with uncertain demands”, Computers & Operations Research, 37(5): 880-889.
[51]Eskandarpour, M., Dejax, P., Miemczyk, J., Péton, O. (2015). “Sustainable supply chain network design: An optimization-oriented review”, Omega, 54: 11-32.
[52] Diabat, A., Richard, J. P. P. (2015). “An integrated supply chain problem: a nested lagrangian relaxation approach”, Annals of Operations Research, 229(1): 303-323.
[53] Fahimnia, B., Jabbarzadeh, A., Ghavamifar, A., Bell, M. (2017). “Supply chain design for efficient and effective blood supply in disasters”, International Journal of Production Economics, 183: 700-709.
[54] Badri, H., Bashiri, M., Hejazi, T. H. (2013). “Integrated strategic and tactical planning in a supply chain network design with a heuristic solution method”, Computers & Operations Research, 40(4): 1143-1154.
[55] Fisher, M. L. (2004). “The Lagrangian relaxation method for solving integer programming problems”, Management science, 50(12_supplement): 1861-1871.
[56] Yadollahinia, M., Teimoury, E., Paydar, M. M. (2018). “Tire forward and reverse supply chain design considering customer relationship management”, Resources, Conservation and Recycling, 138: 215-228. | ||
|
Statistics Article View: 758 PDF Download: 688 |
||