Abstract
An effective closed-loop supply chain (CLSC) is increasingly important for corporate sustainable development, where used products are returned, remanufactured and/or recycled. Optimized planning of CLSC network is required and is influenced by uncertainties of recovery. So, this study seeks to establish a robust optimal model for CLSC network, considering both uncertainties in quantity and quality of returned products. After the general framework of CLSC is discussed, the measurements for uncertain quantity and quality of returned products are formulated mathematically, respectively as a number of discrete scenarios and Quality Index. A mixed integral linear programming (MILP) model for a CLSC network design is established and then translated into a robust optimization model based on regret value, to determine facilities’ locations and quantity of flows between facilities in the network. A numerical example is given, and the simulation results show that the operation strategies of the CLSC are relatively stable under different recycling scenarios. Therefore, the optimization model for CLSC network has good robustness.
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References
Vahdani, B., Mohammadi, M.: A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system. Int. J. Prod. Econ. 170(A), 67–87 (2015)
Inderfurth, K.: Impact of uncertainties on recovery behavior in a remanufacturing environment: a numerical analysis. Int. J. Phys. Distrib. Logist. Manag. 35(5), 318–336 (2005)
Prakash, S., Soni, G., Rathore, A.P.S.: Embedding risk in closed-loop supply chain network design: case of a hospital furniture manufacturer. J. Model. Manag. 12(3), 551–574 (2017)
Khalilzadeh, M., Derikvand, H.: A multi-objective supplier selection model for green supply chain network under uncertainty. J. Model. Manag. 13(3), 605–625 (2018)
Karimi, B., Niknamfar, A.H., Gavyar, B.H., Barzegar, M., Motashami, A.: Multi-objective multi-facility green manufacturing closed-loop supply chain under uncertain environment. Assem. Autom. (2019). https://doi.org/10.1108/AA-09-2018-0138
Durach, C.F., Wieland, A., Machuca, J.A.D.: Antecedents and dimensions of supply chain robustness: a systematic literature review. Int. J. Phys. Distrib. Logist. Manag. 45(1/2), 118–137 (2015)
Klibi, W., Martel, A., Guitouni, A.: The design of robust value-creating supply chain networks: a critical review. Eur. J. Oper. Res. 203(2), 283–293 (2010)
Ben-Tal, A., Nemirovski, A.: Robust optimization – methodology and applications. Math. Program. 92, 453–480 (2002)
Hosseini, S., Farahani, R.Z., Dullaert, W., Raa, B., Rajabi, M., Bolhari, A.: A robust optimization model for a supply chain under uncertainty. J. Manag. Math. 25(4), 387–402 (2014)
Pishvaee, M.S., Rabbani, M., Torabi, S.A.: A robust optimization approach to closed-loop supply chain network design under uncertainty. Appl. Math. Model. 35(2), 637–649 (2011)
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Wang, C., Jiang, H., Luo, Q., Li, S. (2019). A Robust Optimization Model for Closed-Loop Supply Chain Network Under Uncertain Returns. In: Milošević, D., Tang, Y., Zu, Q. (eds) Human Centered Computing. HCC 2019. Lecture Notes in Computer Science(), vol 11956. Springer, Cham. https://doi.org/10.1007/978-3-030-37429-7_40
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DOI: https://doi.org/10.1007/978-3-030-37429-7_40
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