[1] Hugos, M. H. (2018). Essentials of supply chain management. John Wiley & Sons.
[2] Ghahremani-Nahr, J., Nozari, H., & Bathaee, M. (2021). Robust box Approach for blood supply chain network design under uncertainty: hybrid moth-flame optimization and genetic algorithm. International journal of innovation in engineering, 1(2), 40–62.
[3] Szmelter Jarosz, A., Ghahremani-Nahr, J., & Nozari, H. (2021). A neutrosophic fuzzy optimisation model for optimal sustainable closed-loop supply chain network during Covid-19. Journal of risk and financial management, 14(11), 519. https://www.mdpi.com/1911-8074/14/11/519
[4] Ghahremani Nahr, J., Pasandideh, S. H. R., & Niaki, S. T. A. (2020). A robust optimization approach for multi-objective, multi-product, multi-period, closed-loop green supply chain network designs under uncertainty and discount. Journal of industrial and production engineering, 37(1), 1–22.
[5] Zhu, Q., & Sarkis, J. (2006). An inter-sectoral comparison of green supply chain management in China: drivers and practices. Journal of cleaner production, 14(5), 472–486.
[6] Taleizadeh, A. A., Haghighi, F., & Niaki, S. T. A. (2019). Modeling and solving a sustainable closed loop supply chain problem with pricing decisions and discounts on returned products. Journal of cleaner production, 207, 163–181.
[7] 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(2), 637–649.
[8] 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.
[9] Saeedi, S., Mohammadi, M., & Torabi, S. (2015). A De Novo programming approach for a robust closed-loop supply chain network design under uncertainty: An M/M/1 queueing model. International journal of industrial engineering computations, 6(2), 211–228.
[10] Mohammed, F., Hassan, A., & Selim, S. Z. (2018). Robust optimization for closed-loop supply chain network design considering carbon policies under uncertainty. International journal of industrial engineering, 25(4), 526–558.
[11] Polo, A., Peña, N., Muñoz, D., Cañón, A., & Escobar, J. W. (2019). Robust design of a closed-loop supply chain under uncertainty conditions integrating financial criteria. Omega, 88, 110–132.
[12] Kim, J., Do Chung, B., Kang, Y., & Jeong, B. (2018). Robust optimization model for closed-loop supply chain planning under reverse logistics flow and demand uncertainty. Journal of cleaner production, 196, 1314–1328.
[13] Darestani, S. A., & Hemmati, M. (2019). Robust optimization of a bi-objective closed-loop supply chain network for perishable goods considering queue system. Computers & industrial engineering, 136, 277–292.
[14] Ghahremani-Nahr, J., Nozari, H., & Najafi, S. E. (2020). Design a green closed loop supply chain network by considering discount under uncertainty. Journal of applied research on industrial engineering, 7(3), 238–266.
[15] Gholizadeh, H., Fazlollahtabar, H., & Khalilzadeh, M. (2020). A robust fuzzy stochastic programming for sustainable procurement and logistics under hybrid uncertainty using big data. Journal of cleaner production, 258, 120640. https://doi.org/10.1016/j.jclepro.2020.120640
[16] Vahdani, B., & Mohammadi, M. (2015). A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system. International journal of production economics, 170, 67–87.
[17] Fathollahi-Fard, A. M., Ahmadi, A., & Al-e-Hashem, S. M. J. M. (2020). Sustainable closed-loop supply chain network for an integrated water supply and wastewater collection system under uncertainty. Journal of environmental management, 275, 111277. https://doi.org/10.1016/j.jenvman.2020.111277
[18] Kalantari Khalil Abad, A. R., & Pasandideh, S. H. R. (2022). Green closed-loop supply chain network design with stochastic demand: A novel accelerated benders decomposition method. Scientia Iranica, 29(5), 2578–2592.
[19] Pishvaee, M. S., & Razmi, J. (2012). Environmental supply chain network design using multi-objective fuzzy mathematical programming. Applied mathematical modelling, 36(8), 3433–3446.
[20] Hamidieh, A., Naderi, B., Mohammadi, M., & Fazli-Khalaf, M. (2017). A robust possibilistic programming model for a responsive closed loop supply chain network design. Cogent mathematics, 4(1), 1329886. https://doi.org/10.1080/23311835.2017.1329886
[21] 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.
[22] 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, 92, 99–135.
[23] Boronoos, M., Mousazadeh, M., & Torabi, S. A. (2021). A robust mixed flexible-possibilistic programming approach for multi-objective closed-loop green supply chain network design. Environment, development and sustainability, 23, 3368–3395.
[24] Sadrnia, A., Ismail, N., Zulkifli, N., Ariffin, M. K. A., Nezamabadi-pour, H., & Mirabi, H. (2013). A multiobjective optimization model in automotive supply chain networks. Mathematical problems in engineering, 2013. https://doi.org/10.1155/2013/823876
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