Designing a Closed-loop Green Supply Chain Network Considering Quality Costs of Raw Materials in a Fuzzy Environment | ||
| Journal of Quality Engineering and Production Optimization | ||
| مقاله 2، دوره 8، شماره 2، اسفند 2023، صفحه 21-56 اصل مقاله (1.61 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22070/jqepo.2024.19090.1279 | ||
| نویسندگان | ||
| Mahya Talebzadeh1؛ Ali Ghodratnama* 1؛ Reza Tavakkoli-Moghaddam2 | ||
| 1Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran | ||
| 2School of Industrial Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran, Iran | ||
| چکیده | ||
| When the reverse supply chain—which comprises the steps involved in bringing a product back into the supply chain, such as its collection, recycling, and destruction—is taken into account alongside the forward supply chain, it becomes evident how important this issue has become in recent years and how social and environmental factors have been taken into account to meet economic demands. This paper presents a five-level closed-loop green supply chain network, considering cost minimization, environmental effects, and time delays in sending products and raw materials. The model is presented under uncertainty of some parameters, considering the particular position of purchased raw materials. The tri-objective fuzzy model is converted into a crisp model using the Jiménez et al. (2007) method. The performance and efficiency of the model are analyzed using the Torabi-Hassini method and the augmented epsilon constraint method. GAMS software provides a numerical illustration of this process. Sensitivity analysis is used to the various degrees of confidence. The augmented epsilon-constrained method outperforms the Torabi-Hassini (TH) method for the first and second objective functions and vice versa for the third objective function. The computational time of the augmented epsilon-constrained method is also less than that of the TH method for all confidence levels. | ||
| کلیدواژهها | ||
| Closed Loop Green Supply Chain؛ Fuzzy Modelling؛ Uncertainty؛ Epsilon Constrained Method | ||
| مراجع | ||
|
Abdallah, T., Farhat, A., Diabat, A., & Kennedy, S. (2012). Green supply chains with carbon trading and environmental sourcing: Formulation and life cycle assessment”. Applied Mathematical Modelling, 36(9), 4271–4285.
Amin, H., S., & Zhang, G. (2013). A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Applied Mathematical Modelling, 37(6), 4165-4176.
Aslani Khiavi, S., & Skandari, S. (2022). The Impact of Time and Time Delay on the Bullwhip Effect in Supply Chains. Journal of Quality Engineering and Production Optimization., 7(2), 1-13.
Bing, X., Bloemh of- Ruwaard, J., Chaabane, A., & Vorst, J. (2015). Global reverse supply chain redesign for household plastic waste under the emission trading scheme. Journal of Cleaner Production, 103, 28-39.
Boskabadi, A., Mirmozaffari, M., Yazdani, R., & Farahani, A. (2022). Design of a distribution network in a multi-product, multi-period green supply chain system under demand uncertainty. Sustainable Operations and Computers, 3, 226-237Boskabadi, Azam., Mirmozaffari, Mirpouya., Yazdani, Reza., Farahani, Ali. (2022). Design of a Distribution Network in a Multi-product, Multi-period Green Supply Chain System Under Demand Uncertainty. Sustainable Operations and Computers, 3, 226-237.
Cardona-Valdées, Y., Alvarez, A., & Pacheco, J. (2014). Metaheuristic procedure for a bi-objective supply chain design problem with uncertainty. Transportation Research Part B, 60, 66-84.
Chen, J. M., & Chang, C. I. (2013). Dynamic pricing for new and remanufactured products in a closed-loop supply chain. International Journal of Production Economics, 146(1), 153-160.
Farrokh, M., Azar, A., Jandaghi, G., & Ahmadi, E. (2023). A novel robust fuzzy stochastic programming for closed loop supply chain network design under hybrid uncertainty. Fuzzy Sets and Systems, 341, 69-91.
Foroozesh, N., & Karimi, B. (2022). Designing a supply chain by considering secondary risks in the case of food industry: an integrated interval type-2 fuzzy approach. Journal of Quality Engineering and Production Optimization., 7(2), 93-106.
Garg, K., Kannan, D., Diabat, A., & Jha, P. C. (2015). A multi-criteria optimization approach to manage environmental issues in closed loop supply chain network design. Journal of Cleaner Production, 100, 297-314Garg K, Kannan D, Diabat A, Jha PC. (2015). A Multi-criteria optimization approach to manage environmental issues in closed loop supply chain network design. Journal of Cleaner Production.
Ghaderi, H., Gitinavard, H., & Mehralizadeh, M. (2020). An intuitionistic fuzzy DEA cross-efficiency methodology with an application to production group decision-making problems. Journal of Quality Engineering and Production Optimization, 5(2), 69-86.
Ghahremani-Nahr, J., Kian, R., & Sabet, E. (2023). 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.
Gholamian, N., Mahdavi, I., & Tavakkoli-Moghaddam, R. (2021). Multi-echelon green open-location-routing problem: A robust-based stochastic optimization approach. Scientia Iranica, 28(2), 985-1000.
Gitinavard, H., Akbarpour Shirazi, M., & Fazel Zarandi, M. H. (2021). A possibilistic programming approach for biomass supply chain network design under hesitant fuzzy membership function estimation. Scientia Iranica. Gholami, F., Paydar, M. M., Hajiaghaei-Keshteli, M., & Cheraghalipour, A. (2021). A possibilistic programming approach for biomass supply chain network design under hesitant fuzzy membership function estimation. Scientia Iranica. In press.
Gitinavard, H., Ghodsypour, S. H., & Akbarpour Shirazi, M. (2019). A bi-objective multi-echelon supply chain model with Pareto optimal points evaluation for perishable products under uncertainty. Scientia Iranica, 26(5), 2952-2970.
Gumte, K. M., Pantula, P. D., Miriyala, S. S., & Mitra, K. (2024). Data-driven robust optimization for handling uncertainty in supply chain planning models. Chemical Engineering Science, 246, 116889.
Hasan-Zadeh, A. (2023). Developing a new formulation and exact solution approach for continuous time optimal control model: application to coordinating a supplier-manufacturer supply chain. Journal of Quality Engineering and Production Optimization, 8(1), 69-86Hasan-Zadeh, A. (2023). Developing a new formulation and exact solution approach for continuous time optimal control model: application to coordinating a supplier-manufacturer supply chain. Journal of Quality Engineering and Production Optimization. Papers in Press.
Hatefi, S. M., & Jolai, F. (2014). Robust and reliable forward–reverse logistics network design under demand uncertainty and facility disruptions. Applied mathematical modelling, 38(9-10), 2630-2647.Hatefi, S.M., Jolai, F. (2013). Robust and Reliable Forward-Reverse Logistics Network Design under Demand Uncertainty and Facility Disruptions, Appl. Math. Modelling.
Hatefi, S. M., Jolai, F., Torabi, S. A., & Tavakkoli-Moghaddam, R. (2015). A credibility-constrained programming for reliable forward–reverse logistics network design under uncertainty and facility disruptions. International Journal of Computer Integrated Manufacturing, 28(6), 664-678.Hatefi, S.M., Jolai, F., Torabi, S.A. Tavakkoli Moghaddam, R. (2014). A credibility constrained programming for reliable forward–reverse logistics network design under uncertainty and facility disruptions.
Hemmati, H., Baradaran Kazemzadeh, R., Nikbakhsh, E., & Nakhai Kamalabadi, I. (2023). Designing a Green-Resilient Supply Chain Network for Perishable Products Considering a Pricing Reduction Strategy to Manage Optimal Inventory: A Column Generation-based Approach. Journal of Quality Engineering and Production Optimization, 8(1)Hemmati, H., Kazemzadeh, R. B., Nikbakhsh, E., & Nakhai Kamalabadi, I. (2023). Designing a green-resilient supply chain network for perishable products considering a pricing reduction strategy to manage optimal inventory: A Column Generation-based Approach. Journal of Quality Engineering and Production Optimization. Papers in Press.
Huang, Y., Wang, K., Zhang, T., & Pang, C. (2016). Green supply chain coordination with greenhouse gases emissions management: a game-theoretic approach. Journal of Cleaner Production, 112, 2004-2014Huang Y, Wang K, Zhang T, Pang C. (2015). Green supply chain coordination with greenhouse gases emissions management: A game-theoretic approach. Journal of Cleaner Production.
Jiménez, M., Arenas, M., & Bilbao, A. (2007). Linear programming with fuzzy parameters: an interactive method resolution. European Journal of Operational Research, 177(3), 1599-1609.
Kalantari Khalil Abad, A. R., & Pasandideh, S. H. R. (2020). A multi-objective model for green closed-loop supply chain design by handling uncertainties in effective parameters. Journal of Quality Engineering and Production Optimization, 5(1), 221-242.
Karimi, R., Ghezavati, V R., & Khalili. D, K. (2015). Optimization of multi-product, multi-period closed loop supply chain under uncertainty in product return rate: case study in Kalleh dairy company. Journal of Industrial and Systems Engineering, 8(3), 95-113.
Karthick, B., & Uthayakumar, R. (2024). A sustainable supply chain model with two inspection errors and carbon emissions under uncertain demand. Cleaner Engineering and Technology, 5, 100307.
Kaya, O., & Urek, B. (2015). A Mixed Integer Nonlinear Programming Model and Heuristic Solutions for Location, Inventory and Pricing Decisions in a Closed Loop Supply Chain. Computers and Operations Research, 65, 93-103.
Kazancoglu, Y., Yuksel, D., Sezer, M. D., Mangla, S. K., & Hua, L. (2022). A green dual-channel closed-loop supply chain network design model. Journal of cleaner production, 332, 130062Kazancoglu, Yigit., Yuksel, Damla., Sezer, Muruvvet Deniz., Mangla, Sachin Kumar., Hua, Lianlian. (2022). A Green Dual-Channel Closed-Loop Supply Chain Network Design Model. Journal of Cleaner Production, 332, 130062.
Keshmiry Zadeh, K., Harsej, F., Sadeghpour, M., & Molani Aghdam, M. (2021). A multi-objective multi-echelon closed-loop supply chain with disruption in the stations. Journal of Quality Engineering and Production Optimization, 6(2), 31-58.
Khorshidvand, B., Soleimani, H., Sibdari, S., & Esfahani, M. M. S. (2021). A hybrid modeling approach for green and sustainable closed-loop supply chain considering price, advertisement and uncertain demands. Computers & Industrial Engineering, 157, 107326Khorshidvand, B., Soleimani, H., Sibdari, S., Esfahani, M.M.S. (2024). A hybrid modeling approach for green and sustainable closed-loop supply chain considering price, advertisement, and uncertain demands. Computers & Industrial Engineering, 157, 107326.
Lotfi, R., Nazarpour, H., Gharehbaghi, A., Sarkhosh, S. M. H., & Khanbaba, A. (2022). Viable closed-loop supply chain network by considering robustness and risk as a circular economy. Environmental Science and Pollution Research, 29(46), 70285-70304Yavari, S., Ajalli, N. (2024). Viable closed-loop supply chain network by considering robustness and risk as a circular economy strategy. Environmental Science and Pollution Research, details pending.
Mavrotas, G. (2009). Effective implementation of the 𝜀 -constraint method in Multi-objective mathematical programming problems. Applied Mathematical Computer, 213, 455-465.
Moayedi, M., & Sadeghian, R. (2023). A multi-objective stochastic programming approach with untrusted suppliers for green supply chain design by uncertain demand, shortage, and transportation costs. Journal of Cleaner Production, 408, 137007.
Mohtashami, Z., Aghsami, A., & Jolai, F. (2020). a green closed-loop supply chain design using the queuing system for reducing environmental impact and energy consumption. Journal of Quality Engineering and Production Optimization, 242, 118452.
Mousazadeh, M., Torabi, S. A., & Zahiri, B. (2015). A robust possibilistic programming approach for pharmaceutical supply chain network design. Computers & Chemical Engineering, 82, 115-128Mousazadeh, M., Torabi, S.A., Zahiri, B. (2015). Robust possibilistic programming approach for pharmaceutical supply chain network design. Computers and Chemical Engineering.
Nasr, A. K., Tavana, M., & Alavi, B. (2020). Strategic planning of renewable distributed generation in radial distribution system using advanced mopso method. Journal of Quality Engineering and Production Optimization, 6(1), 2872-2886.
Özceylan, E., Paksoy, T., & Bektaş, T. (2014). Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing. Transportation research part E: logistics and transportation review, 61, 142-164.Özceylan E, Paksoy T, Bektaş T. (2013). Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing. Transportation Research Part E: Logistics and Transportation Review.
Pasandideh, S. H. R., Niaki, S. T. A., & Asadi, K. (20142015). Optimizing a bi-objective multi-product multi-period three echelon supply chain network with warehouse reliability. Expert Systems with Applications, 42(5), 2615-2623.
Pishvaee, M.S., & Razmi, J. (2011). Environmental supply chain network design using multi-objective fuzzy mathematical programming. Applied Mathematical Modelling, 36, 3433-3446.
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, 2668-2683.
PrasannaVenkatesan, S., & Kumanan, S. (2012). Multi-objective supply chain sourcing strategy design under risk using PSO and simulation. The International Journal of Advanced Manufacturing Technology, 61, 325-337. Venkatesan, Prasanna, S., Kumanan, S. (2011). Multi-objective supply chain sourcing strategy design under risk using PSO and simulation. International Journal of Advanced Manufacturing Technology, 61, 325-337.
Quan, S., & Guo, C. (2023). A fuzzy robust programming model for sustainable closed-loop supply chain network design with efficiency-oriented multi-objective optimization. Processes, 10(10), 1963.
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.
Solgi, E., Gitinavard, H., & Tavakkoli-Moghaddam, R. (2021). Sustainable high-tech brick production with energy-oriented consumption: An integrated possibilistic approach based on criteria interdependencies. Sustainability, 14(1), 202.
Tehrani, M., & Gupta, S. M. (2021). Designing a sustainable green closed-loop supply chain under uncertainty and various capacity levels. Logistics, 5(2), 20Tehrani., Mohsen, Gupta., Surendra M. (2021). Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels. Journals, Logistics , 5(2).
Vahdani, B., Tavakkoli-Moghaddam, R., Jolai, F. & Baboli, A. (2013). Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model. Engineering Optimization, 45(6), 745-765.
Winkler, H. (2011). Closed-loop production systems- A sustsinsble supply chain approach. CIRP Journal of Manufacturing Science and Technology, 4(3), 243-246.
Yang, P. C., Chung, S. L., Wee, H. M., Zahara, E., & Peng, C. Y. (2013). Collaboration for a closed-loop deteriorating inventory supply chain with multi-retailer and price-sensitive demand. International Journal of Production Economics, 142(2), 557- 566.
Zeballos, L. J., Méndez, 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, 151-164Zeballos, Luis J., M´endez, Carlos A., P.Barbosa-Povoa, A., Q. Novais, A. (2014). Multi-period design and planning of closed-loop supply chains with uncertain supply and demand.
Zhen, L., Huang, L., & Wang, W. (2019). Green and sustainable closed-loop supply chain network design under uncertainty. Journal of Cleaner Production, 227, 1195-1209Zhen, Lu., Huang, Lufei., Wang, Wencheng. (2019). Green and sustainable closed-loop supply chain network design under uncertainty. Journal of Cleaner Production, 227, 1195-1209. | ||
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