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Integration of supplier selection and resilient closed loop supply chain design and ranking based on fuzzy-MOORA-reference point method

Document Type : Research Paper

Authors

1 Associate Professor, Department of Industrial Engineering, Faculty of Engineering, Al-Zahra University, Tehran, Iran

2 Master's Degree, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other criteria except for price, like the production process, the features of parts and reliability of supply have long term effects on the performance of supply chains. In this research a general closed loop supply chain network including production centres, disassembly, refurbishing, and disposal sites is considered. An integrated two-phase model is given so that in the first phase, the proposed fuzzy-MOORA-reference point method is applied to suppliers’ assessment and the results from this phase is used in the second phase. In the second phase, a three-objective mixed integer linear programming model is proposed in order to determine the eligible suppliers, the locations of refurbishing sites and the material flows between the supply chain members. The objective functions are maximizing profit, suppliers’ evaluation and resiliency scores. Unsatisfied demand of customers is lost. The numerical results show the validity of the model and the role of stockout option in reaching better solutions based on the LP-Metric method.

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References
بشیری، مهدی؛ شیری، مهدیه (1394)، طراحی شبکه زنجیره تأمین حلقه بسته با در نظر گرفتن مراکز جمع‌آوری چندبخشی در شرایط عدم قطعیت و حل آن با دو الگوریتم ابتکاری و فرا ابتکاری، پژوهش‌های مهندسی صنایع در سیستم‌های تولید، دوره 3، شماره 5، صفحات 27-41.
بشیری، مهدی؛ شرافتی، مهتاب (1392)، طراحی دو هدفه شبکه زنجیره تأمین حلقه بسته با در نظر گرفتن معیارهای همبسته در محیط فازی، پژوهش‌های مهندسی صنایع در سیستم‌های تولید، دوره 1، شماره 1، صفحات 25-35.
حیدری، صدف (1399)، ارائه یک مدل برنامه‌ریزی دو هدفه برای انتخاب تأمین‌کننده در زنجیره تأمین تاب آور تحت ریسک‌های عملیاتی و اختلالات، پایان‌نامه کارشناسی ارشد دانشگاه الزهرا.
کمالی، حمیدرضا؛ صادقیه، احمد؛ وحدت زاد، محمدعلی؛ خادمی زارع، حسن (1394)، برنامه‌ریزی زنجیره تأمین حلقه بسته با تقاضای قطعی پویا و قیمت پیوسته نزولی، مجله مهندسی صنایع و مدیریت، دوره 31-1، شماره 2/2، صفحات 51-60.
آذر، عادل؛ کولیایی، مریم؛ امینی، محمدرضا؛ رجب‌زاده قطری، علی (1395)، طراحی مدل ریاضی یکپارچه برای زنجیره تأمین با حلقه بسته، پژوهش‌های مدیریت در ایران، دوره 20، شماره 1، صفحات 1-28.
Abdolazimi, O., Salehi Esfandarani, M., Salehi, M., Shishebori, D. (2020). Robust design of a multi-objective closed-loop supply chain by integrating on-time delivery, cost, and environmental aspects, case study of a Tire Factory. Journal of Cleaner Production, Vol. 226, pp. 988-1003.
Ahmadi, S., Amin, S.H. (2019). An integrated chance-constrained stochastic model for a mobile phone closed-loop supply chain network with supplier selection. Journal of Cleaner Production, Vol. 226, pp. 988-1003.
Amin, S.H., Razmi, J. (2009). An integrated fuzzy model for supplier management: A case study of ISP selection and evaluation. Expert Systems with Applications, Vol. 36, No. 4, pp. 8639-8648.
Amin, S.H., Razmi, J., Zhang, G. (2011). Supplier selection and order allocation based on fuzzy SWOT analysis and fuzzy linear programming. Expert Systems with Applications, Vol. 38, No. 1, pp. 334–342.
Amin, S.H., Zhang, G. (2012). An integrated model for closed-loop supply chain configuration and supplier election: multi-objective approach. Expert Systems with Applications, Vol. 39, No. 1, pp. 6782–6791.
Brauers, W., Zavadskas, E.K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, Vol. 35, No. 2, pp. 445-469.
Fleischmann, M., Bloemhof-Ruwarrd, J. M., Dekker, R., Der Lann, E., Nunen, J.A.E.E., Wassenhove, L. N. (1997). Quantitative models for reverse logistics: A review. European Journal of Operational Research, Vol. 103, No. 1, pp. 1–17.
Ghahremani-Nahr, J., Kian, R., Sabet, E. (2019). A robust fuzzy mathematical programming model for the closed-loop supply chain network design and a whale optimization solution algorithm. Expert Systems with Applications, Vol. 116, pp. 454-471.
Ghayebloo, S., Tarokh, M.J., Venkatadri, U., Diallo, C. (2015). Developing a bi-objective model of the closed-loop supply chain network with green supplier selection and disassembly of products: The impact of parts reliability and product greenness on the recovery network. Journal of Manufacturing Systems, Vol. 36, pp. 76-86.
Govindan, K., Dhingra Darbari, J., Agarwal, V., Jha, P.C. (2017). Fuzzy multi-objective approach for optimal selection of suppliers and transportation decisions in an eco-efficient closed loop supply chain network. Journal of Cleaner Production, Vol. 165, pp. 1598-1619.
Govindan, K., Mina, H., Esmaeili, A., Gholami-Zanjani, S.M. (2020). An Integrated Hybrid Approach for Circular supplier selection and Closed loop Supply Chain Network Design under Uncertainty. Journal of Cleaner Production, Vol. 242, 118317.
Guide Jr., V.D.R., Van Wassenhove, L.N. (2009). The evolution of closed-loop supply chain research. Operations Research, Vol. 57, No. 1, pp. 10–18.
Haddad-Sisakht, A., Ryan, S.M. (2018). Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax. International Journal of Production Economics, Vol.195, pp.118-131.
Li, B., Wang, Y., Wang, Z. (2021). Managing a closed-loop supply chain with take-back legislation and consumer preference for green design. Journal of Cleaner Production, Vol. 282, 124481.
Liu, Y., Ma, L., & Liu, Y. (2021). A novel robust fuzzy mean-UPM model for green closed-loop supply chain network design under distribution ambiguity. Applied Mathematical Modelling, Vol. 92, pp. 99-135.
Bhatia, M.S., Jakhar, S.K., Mangla, S.K., Gangwani, K.K. (2020). Critical factors to environment management in a closed loop supply chain. Journal of Cleaner Production, Vol. 255, 120239.
Melo, M. T., Nickel, S., & Saldanha-da-Gama, F. (2009). Facility location and supply chain management – A review. European Journal of Operational Research, Vol.196, No. 2, pp. 401–412.
Pazhani, S., Mendoza, A., Nambirajan, R., Narendran, T.T., Ganesh, K., Olivares-Benitez, E. (2021). Multi-period multi-product closed loop supply chain network design: A relaxation approach. Computers & Industrial Engineering, Vol. 155, 107191.
Pokharel, S., & Mutha, A. (2009). Perspectives in reverse logistics: A review. Resources, Conservation and Recycling, Vol. 53, No. 4, pp. 175–182.
Pourmehdi, M., Paydar, M.M., Asadi-Gangraj, E. (2020). Scenario-based design of a steel sustainable closed-loop supply chain network considering production technology. Journal of Cleaner Production, Vol. 277, 123298.
Shakourloo, A., Kazemi, A., & Oroojeni Mohammad Javad, M. (2016). A new model for more effective supplier selection and remanufacturing process in a closed-loop supply chain. Applied Mathematical Modelling, Vol. 40 (23-24), 9914-9931.
Soleimani, H., Govindan, K., Saghafi, H., & Jafari, H. (2017). Fuzzy multi-objective sustainable and green closed-loop supply chain network design. Computers & Industrial Engineering, Vol. 109, pp. 191-203.
Bashiri, M., & Shiri, M. (2015). Design of closed-loop supply chain network with considering of multi-part collection centers under uncertainty with two heuristic and meta-heuristic algorithms. Journal of Industrial Engineering Research in Production Systems, Vol. 3, No. 5, pp. 27–41. [In Persian]
Bashiri, M., & Sherafati, M. (2013). Advanced Bi-objective closed loop supply chain network design considering correlated criteria in fuzzy environment. Journal of Industrial Engineering Research in Production Systems, Vol. 1, No. 1, pp. 25–36. [In Persian]
Heydari, Sadaf. (2020). Proposing a bi-objective programming model for supplier selection in resilient supply chain under operational risks nd disruptions. MSc thesis, Alzahra University. [In Persian]
Kamali, H.R., Sadeghieh, A., Vahdat-Zad, M.A., & Khademi-Zare, H. (2016). P‌lanning closed loop supply chain with dynamic deterministic demand and‌ continuous price decrease. Industrial Engineering and Management. Vol. 31.1, No. 2.2, pp. 27–35. [In Persian]
Azar, A., Kolyaei, M., Amini, M.H., & Rajabzadeh Gatari, A. (2016). Design of integrated mathematical model for closed-loop supply chain. Management Research in Iran. Vol. 20, No. 1, pp. 1–32. [In Persian]
Industrial Management Studies
Volume 20, Issue 65
June 2022
Pages 1-37
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