A robust fuzzy optimization model for designing close-loop green supply chain network under possibility chance constraint programming

Document Type : Research Paper

Authors

1 Industrial Engineering Department, Faculty of Engineering, Yazd University, Yazd, Irab

2 Industrial Engineering Department, Faculty of Engineering, Yazd University, Yazd, Iran

3 yazd University

Abstract

Nowadays environmentalism has been become an important global issue. In recent years, the closed-loop green supply chain management has grown considerably and its result be important for managers. In this paper, we have proposed a mathematical optimization mixed-integer programming model for designing a single objective closed-loop green supply cahin network consisting of production and recovery centers, distribution centers, inspection centers,disposal centers and customers, which, in addition to reducing system costs includes the fixed cost of openning plant and distribution centers, the variable cost of product production with different technologies and shipping cost, taking into the carbon tax rate, the amount of carbon emissioned by production, transportation and establishing. Due to in real-world issue the parameters are uncertain. Moreover, the model has been developed using a robust fuzzy programming approach to examine the effects of uncertainties of production cost, remanufacturing cost,distribution process cost, inspection process cost and disposal process cost, amount carbon emission, facility capacity and the demand rate on the network design. Gams software has been used to obtain an optimal solution to the problem. The numerical results shows the proposed model is capable of controlling uncertainty and the robustness price is imposed on the system, therefore, the value of the objective function in a probability 5% is lower than the robust fuzzy possibilistic.

Keywords

References

[1] Ramezani, M., Kimiagari, A.M., Karimi, B., Hejazi, T.H., (2014). “Closed-loop supply chain network design under a fuzzy environment”, Knowledge-Based Systems, 59: 108-120.
[2] Alem, D. J., Morabi, R., (2012). “Production planning in furniture settings via robust optimization”, Computers & Operations Research,39(2): 139-150.
]3[ کلانتری، پیشوایی، (1395). "یک مدل برنامه‌ریزی استوار امکانی برای برنامه‌ریزی اصلی زنجیره تامین دارو"، نشریه پژوهش­های مهندسی صنایع در سیستم­های تولید، 4(7): 49-67.
[4] Melnyk, S.A., Narasimhan, R., Decampos, H.A., (2014). “Supply chain design: issues, challenges,33 frameworks and solutions”, International Journal of Production Research, 52 (7): 1887-1896.
[5] Üster, H., Easwaran, G., Akçali, E., Çetinkaya, S., (2007). “Benders decomposition with alternative multiple cuts for a multi-product closed-loop supply chain network design model”, Naval Research Logistics, 54 (8): 890-907
[6] Validi, S., Bhattacharya, A., Byrne, P.J., (2015). “A solution method for a two-layer sustainable supply chain distribution model”, Computers & Operations Research, 54: 204-217
[7] Pishvaee, M.S., Torabi, S.A., (2010). “A possibilistic programming approach for closed-loop supply chain network design under uncertainty”, Fuzzy Sets and Systems, 161(20): 2668-2683.
[8] Wang, C., Wang, W., Huang, R., (2017). “Supply chain enterprise operations and government carbon tax decisions considering carbon emissions”, Journal of Cleaner Production, 152: 271-280.
[9] Nurjanni, K.P., Carvalho, M.S., Costa, L., (2017). “Green supply chain design: a mathematical modeling approach based on a multi-objective optimization model”, International Journal of  Production Economic, 183: 421-32.
[10] Mohtashami, Z., Aghsami, A., Jolai, F. (2020). “A green closed loop supply chain design using queuing system for reducing environmental impact and energy consumption”, International Journal of Cleaner Production, 242: 118452-118471.
[11] Zhen, L., Huang, L., Wencheng W., (2019). “Green and Sustainable Closed-Loop Supply Chain Network Design under Uncertainty”, International Journal of Cleaner Production, 227: 1195-1209.
[12] Matsumoto, M., Chinen, K., Endo, H. (2018). “Remanufactured auto parts market in Japan: Historical review and factors affecting green purchasing behavior”, International Journal of Cleaner Production, 172: 4494-4505.  
[13] Reza Sadeghi Rad, Nasim Nahavandi., (2018). “A novel multi-objective optimization model for integrated problem of green closed loop supply chain network design and quantity discount’. International Journal of Cleaner Production. 196: 1549-1565
[14] Talaei, M., Moghaddam, B.F., Pishvaee, M.S., Bozorgi-Amiri, A., Gholamnejad, S., (2016). A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry”, International Journal of J. Cleaner Production, 113: 662-673.
[15] Govindan, K., Darbari, J.D., 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”, International Journal of Cleaner Production, 165: 1598-1619.
[16] Rabieh M., Azar A., Modarres Yazdi M., Fetanat Fard Haghighi M. (2011) “Designing a multi-objective robust multi-sourcing mathematical model, An approach for reducing the risk of supply chain (Case study: Supply Chain of IRAN KHODRO Company)”; Industrial Management's Perspective, 1: 57-77, (in Persian).
[17] Pishvaee, M.S., Razmi, J., and Torabi, S., (2012). “Robust possibilistic programming for socially responsible supply chain network design: A new approach”, Fuzzy sets and systems, 206: 1-20
[18] Zahiri, B.,Tavakkoli Moghaddam, R., Pishvaee, M.S., (2014). “A robust possibilistic programming approach to multi-period location--allocation of organ transplant centers under uncertainty”, Computers & Industrial Engineering 74: 139-148.
[19] Ayvaz, B., Bolat, B., Aydın, N., (2015). “Stochastic reverse logistics network design for waste of electrical and electronic equipment”, Resources Conservation and Recycling. 104: 391-404.
[20] 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”, Europe Journal of Operation Research, 179 (3): 1063-1077.
[21] Ramezani, M., Bashiri, M., Tavakkoli-Moghaddam, R., (2013). “A robust design for a closed-loop supply chain network under an uncertain environment”, International Journal of  AdvancedManufacturing Technology, 66(5-8): 825-843.
[22] Zeballos, L.J., Mendez, C.A., Barbosa-Povoa, A.P., Novais, A.Q., (2014). “Multi-period  design and planning of closed-loop supply chains with uncertain supply and demand”, Computers & Chemical Engineering, 66: 151-164.
[23] Subulan, K., Tas¸ an, A.S., Baykasoglu, A., (2015). “A fuzzy goal programming model to  strategic planning problem of a lead/acid battery closed-loop supply chain”, Journal of Manufacturing System, 37: 243-264.
[24] Xu, J., Yao, L., Zhao, X., (2011). “A multi-objective chance constrained network optimal model withrandom fuzzy coefficients and its application to logistics distribution center location problem”. Fuzzy Optimization and Decision Making, 10: 255-285.
[25] Wang, H.F., Hsu, H.W., (2012). “A possibilistic approach to the modeling and resolution of uncertain closed-loop logistics”, Fuzzy Optimization and Decision Making 11: 177-208.
[26] Pinto-Varela, T., Barbosa-Povoa, A.P.F.D., Novais, A.Q., (2011). “Bi-objective optimization approach to the design and planning of supply chains: Economic versus environmental performances”, Computers & Chemical Engineering 35, 1454-1468.
[27] Safaei, A.S., Roozbeh, A., Paydar, M.M., (2017). “A robust optimization model for the design of a cardboard closed-loop supply chain”, International Journal of Cleaner Production, 166: 1154-1168.
[28] Yu-Chung Tsao, Vo-Van Thanh, Jye-Chyi Lu, Vincent Yu., (2018). “Designing sustainable supply chain networks under uncertain environments: Fuzzy multi-objective programming”, International Journal of Cleaner Production. 174: 1550-1565.
]29 [ پاپی، علی، پیشوایی، میرسامان، جبارزاده، آرمین، قادری، سید فرید، (1397). "برنامه ریزی بهینه استوار زنجیره عرضه نفت خام و توسعه بهینه میادین نفتی در شرایط عدم قطعیت: مطالعه موردی شرکت ملی نفت خیز جنوب ایران"، فصلنامه مطالعات اقتصاد انرژی،14(58):۲۷-۶۴.
]30[ فرخ، مجتبی، آذر، عادل، جندقی، امیرعلی (1395). "توسعه رویکرد برنامه ریزی فازی استوار برای طراحی زنجیره تامین حلقه بسته"، چشم انداز مدیریت صنعتی، 1(3):131-160.
]31[ جبل عاملی، محمد سعید، بزرگی امیری، علی، حیدری، مهدی، (1390). "ارائه مدل برنامه‌ریزی امکانی چند هدفه برای مسئله لجستیک امداد"، نشریه بین‌المللی مهندسی صنایع و مدیریت تولید دانشگاه علم و صنعت ایران، 22(1) : 66-76.
]32[ علینقیان، مهدی، ره افروز، مریم. (1396). "مدلسازی پایدار لجستیک امداد در شرایط وجود عدم قطعیت با استفاده از مدل امکانی محدودیت شانس"، نشریه بین‌المللی مهندسی صنایع و مدیریت تولید دانشگاه علم و صنعت ایران، 28(2): 256-270.
]33[ زارعیان جهرمی،  حسین، فلاح نژاد،  محمد صابر، صادقیه، احمد، احمدی یزدی، احمد. (1393). " مدل بهینه سازی چند هدفه استوار در طراحی زنجیره تأمین حلقه بسته پایدار"، نشریه پژوهش­های مهندسی صنایع در سیستم­های تولید، 2(3): 111-93.
[34] 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, 116: 454-471.
[35] Emirhüseyinoğlu, G., Ekici, A., (2019). “Dynamic facility location with supplier selection under quantity discount”, Computers & Industrial Engineering, 134: 64-74.
[36] Pishvaee, M.S., Rabbani, M., Torabi, S.A., (2011). “A robust optimization approach to closed-loop supply chain network design under uncertainty”, Applied Mathematical Modelling 35: 637-649.
[37] Liu, B., Iwamura, K., (1998). “Chanceconstrained programming with fuzzy parameters”, Fuzzy Sets and Systems, 94: 227-237.
[38] Gupte, A., Ahmmed, S., Cheon,M.S., Dey, S., (2013). “Solving Mixed Integer Bilinear Problems Using MILP Formulation”, SIMA Journal on optimization, 23(2): 721-744
Journal of Industrial Engineering Research in Production Systems
Volume 7, Issue 15
March 2020
Pages 273-285

Files

Share

How to cite

Statistics