[1] Dai, Z., Zheng, X. (2015). Design of close-loop supply chain network under uncertainty using hybrid genetic algorithm: A fuzzy and chance-onstrained programming model. Computers & Industrial Engineering, 88, 444-457. doi:http://dx.doi.org/10.1016/j.cie.2015.08.004
[2] Ramezani, M., Kimiagari, A. M., Karimi, B. (2014). Closed-loop supply chain network design: A financial approach. Applied Mathematical Modelling, 38 (15–16), 4099-4119. doi:http://dx.doi.org/10.1016/j.apm.2014.02.004
[3] Kaya, O., Urek, B. (2016). A mixed integer nonlinear programming model and heuristic solutions for location, inventory and pricing decisions in a closed loop supply chain. Computers & Operations Research, 65, 93-103. doi:http://dx.doi.org/10.1016/j.cor.2015.07.005
[4] Khalifehzadeh, S., Seifbarghy, M., Naderi, B. (2015). A four-echelon supply chain network design with shortage: Mathematical modeling and solution methods. Journal of Manufacturing Systems, 35, 164-175. doi:http://dx.doi.org/10.1016/j.jmsy.2014.12.002
[5] Amin, S. H., & 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. doi:http://dx.doi.org/10.1016/j.apm.2012.09.039
[6] Aydin, R., Kwong, C. K., & Ji, P. (2016). Coordination of the closed-loop supply chain for product line design with consideration of remanufactured products. Journal of Cleaner Production, 114, 286-298. doi:http://dx.doi.org/10.1016/j.jclepro.2015.05.116
[7] Ramezani, M., Kimiagari, A. M., Karimi, B., Hejazi, T. H. (2014). Closed-loop supply chain network design under a fuzzy environment. Knowledge-Based Systems.
[8] 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. doi:http://dx.doi.org/10.1016/j.apm.2013.11.002
[9] Cardoso, S. R., Barbosa-Póvoas, A. P. F. D., Relvas, S., Novais, A. Q. (2014). Resilience assessment of supply chains under different types of disruption. In J. D. S. Mario R. Eden & P. T. Gavin (Eds.), Computer Aided Chemical Engineering (Vol. Volume 34, pp. 759-764): Elsevier.
[10] Alshamsi, A., Diabat, A. (2015). A reverse logistics network design. Journal of Manufacturing Systems, 37, Part 3, 589-598. doi:http://dx.doi.org/10.1016/j.jmsy.2015.02.006
[11] Teimuory, E., Bozorgi Atoei, F., Mohammadi, E., Bozorgi Amiri, A. (2013). A multi-objective reliable programming model for disruption in supply chain. Management Science Letters, 3(5), 1467-1478.
[12] Cardona-Valdés, Y., Álvarez, A., Pacheco, J. (2014). Metaheuristic procedure for a bi-objective supply chain design problem with uncertainty. Transportation Research Part B: Methodological, 60, 66-84. doi:http://dx.doi.org/10.1016/j.trb.2013.11.010
[13] Kalaitzidou, M. A., Longinidis, P., & Georgiadis, M. C. (2015). Optimal design of closed-loop supply chain networks with multifunctional nodes. Computers & Chemical Engineering, 80, 73-91. doi:http://dx.doi.org/10.1016/j.compchemeng.2015.05.009
[14] Karimi, R., Ghezavati, V. R., & Damghani, K. 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.
[15] Mousazadeh, M., Torabi, S. A., & Zahiri, B. (2015). A robust possibilistic programming approach for pharmaceutical supply chain network design. Computers & Chemical Engineering,82,115-128. doi:http://dx.doi.org/10.1016/j.compchemeng.2015.06.008
[16] Pasandideh, S. H. R., Niaki, S. T. A., & Asadi, K. (2015). Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA. Information Sciences, 292, 57-74.doi:http://dx.doi.org/10.1016/j.ins.2014.08.068
[17] 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. Int. J. Comput. Integr. Manuf., 28(6), 664-678. doi:10.1080/0951192x.2014.900863
[18] 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. doi:http://dx.doi.org/10.1016/j.tre.2013.11.001
[19] Pishvaee, M. S., Razmi, J., Torabi, S. A. (2014). An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain. Transportation Research Part E: Logistics and Transportation Review, 67, 14-38. doi:http://dx.doi.org/10.1016/j.tre.2014.04.001
[20] 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, 151-164. doi:http://dx.doi.org/10.1016/j.compchemeng.2014.02.027
[21] Amin, S. H., Zhang, G. (2012). An integrated model for closed-loop supply chain configuration and supplier selection: Multi-objective approach. Expert Systems with Applications, 39(8), 6782-6791. doi:http://dx.doi.org/10.1016/j.eswa.2011.12.056
[22] Pishvaee, M. S., Razmi, J. (2012). Environmental supply chain network design using multi-objective fuzzy mathematical programming. Applied Mathematical Modelling, 36(8), 3433-3446. doi:http://dx.doi.org/10.1016/j.apm.2011.10.007
[23] Vahdani, B., Tavakkoli-Moghaddam, R., Jolai, F., & Babolib, A. (2012). Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model. Engineering Optimization, 45(6), 745-765
[24] El-Sayed, M., Afia, N., El-Kharbotly, A. (2010). A stochastic model for forward–reverse logistics network design under risk. Computers&Industrial Engineering, 58(3), 423-431. doi:http://dx.doi.org/10.1016/j.cie.2008.09.040
[25] Ramezani, M., Bashiri, M., Tavakkoli-Moghaddam, R. (2013). A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level. Applied Mathematical Modelling, 37(1–2), 328-344. doi:http://dx.doi.org/10.1016/j.apm.2012.02.032
[26] A Ebrahimy Zade, Fakhrzad, M.B., 2013, A dynamic genetic algorithm for solving a single machine scheduling problem with periodic maintenance. ISRN Industrial Engineering. 21(4), 211-220.
[28] Fakhrzad, M.B., Heydari, M., (2008). A Heuristic Algorithm for Hybrid Flow-shop Production Scheduling to Minimize The Sum of The Earliness ANDF Tardiness Costs. Journal of the Chinese Institute of Industrial Engineers, 25(2), 105-115.
[30] Fakhrzad, M.B., Moobed, M., (2010). A GA model development for decision making under reverse logistics. International Journal Of Industrial Engineering And Production Research,21, 4, 211-220.
[32] Fakhrzad, M.B., Sadri Esfahanib, A., (2013). Modeling the time windows vehicle routing problem in cross-docking strategy using two meta-heuristic algorithms. International Journal of Engineering-Transactions A: Basics, 27, 7,1113-1126.
[33] Jimenez, M., Arenas, M., Bilbao, A. & Guez, M. V. (2007). “Linear programming with fuzzy parameters: an interactive method resolution.” European Journal of Operational Research, 177, 1599-1609.
[34] Torabi, S.A., Hassini, E. (2008). “An interactive possibilistic programming approach for multiple objective supply chain master planning”. Fuzzy Sets and Systems. 159(2(, 193-214.
[35] Sahebjamnia, N., Goodarzian, F., & Hajiaghaei-Keshteli, M. (2019). Optimization of Multi-Period Three-echelon CitrusSupply Chain Problem. Journal of Optimization in Industrial Engineering, 41-50.
[36] Fakhrzad, M. B., Goodarzian, F. (2019). A Fuzzy Multi-Objective Programming Approach to Develop a Green Closed-Loop Supply Chain Network Design Problem under Uncertainty: Modifications of Imperialist Competitive Algorithm. RAIRO-Operations Research, 53(3), 963-990.
[37] Goodarzian, F., Hosseini-Nasab, H. (2019). Applying a fuzzy multi-objective model for a production–distribution network design problem by using a novel self-adoptive evolutionary algorithm. International Journal of Systems Science: Operations & Logistics, 1-22.
[38] Fakhrzad, M. B., Talebzadeh, P., Goodarzian, F. (2018). Mathematical Formulation and Solving of Green Closed-loop Supply Chain Planning Problem with Production, Distribution and Transportation Reliability. International Journal of Engineering, 31(12), 2059-2067.
]27[ خسروشاهی، حسین، معطرحسینی، سید محمد، مرجانی، محمدرضا (1393). "اندازه گیری اثر شلاق چرمی در یکزنجیره تأمین خطی سه سطحی با استفاده از روش میانگین متحرک برای برآورد تقاضا". نشریه پژوهشهای مهندسی صنایع در سیستمهای تولید، 2(4)، 21-37.
]29[ لطفی، رضا، امین نیری، مجید (1395). "مکانیابی تسهیلات چند هدفه با محدودیت ظرفیت و رویکرد ترکیبی سیمپلکس فازی و الگوریتم ژنتیک". نشریه پژوهشهای مهندسی صنایع در سیستمهای تولید، 4(7)، 81-91.
]31[ نخعی، عیسی، محمدی پور، هیرش، ذگردی، سید حسام الدین (1393). "تعیین سود بهینه فروشنده برای محصولات جایگزین و مکمل به کمک قیمت گذاری و در نظر گرفتن سیاست فروش بستهای و تخفیف". نشریه پژوهشهای مهندسی صنایع در سیستمهای تولید، 2(4)، 99-113.
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