Abdel-Basset, M., & Mohamed, R. (2020). A novel plithogenic TOPSIS-CRITIC model for sustainable supply chain risk management. Journal of Cleaner Production, 247, 119586
Aghaei, J., Amjady, N., & Shayanfar, H. A. (2011). Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method. Applied Soft Computing, 11(4), 3846-3858.
Agahgolnezhad Gerdrodbari, M., Harsej, F., Sadeghpour, M., Molani Aghdam, M. (2021). A green CLSC for production and distribution of perishable products. Journal of Quality Engineering and Production Optimization, 6(1), 189-214. doi: 10.22070/jqepo.2021.14469.1184
Ali, S. S., Paksoy, T., Torğul, B., & Kaur, R. (2020). Reverse logistics optimization of an industrial air conditioner manufacturing company for designing sustainable supply chain: a fuzzy hybrid multi-criteria decision-making approach. Wireless Networks, 1-24.
Al-Qudaimi, A., Kaur, K., Bhat, S. (2021). Triangular Fuzzy Numbers Multiplication: QKB method. Fuzzy Optimization and Modeling Journal, 2(2), 34-40.
Alzoubi, H., Ahmed, G., Al-Gasaymeh, A., & Kurdi, B. (2020). An empirical study on sustainable supply chain strategies and its impact on competitive priorities: The mediating role of supply chain collaboration. Management Science Letters, 10(3), 703-708.
Biuki, M., Kazemi, A., & Alinezhad, A. (2020). An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network. Journal of Cleaner Production, 120842.
Coello, C. C. A. , Pulido, G. , & Lechuga, M. (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8, 256–279.
Czyzak, P., Jaszkiewicz, A. (1998). Pareto simulated annealing a metaheuristic for multiobjective combinatorial optimization. Journal of Multi-Criteria Decision Analysis, 7, 1, 34˚ 47.
D.G. Mogale, Arijit De, Abhijeet Ghadge, Emel Aktas,(2022), Multi-objective modeling of sustainable closed-loop supply chain network with price-sensitive demand and consumer’s incentives, Computers & Industrial Engineering, Volume 168, 108105
Deb, K., Pratap, A., Agrawal, S., & Meyarivan, T. (2002). Fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transaction on Evolutionary Computation 6(2), 182-197
Dijkman, J.G., Van Haeringen, H., De Lange, S.J., Zadeh, L. (1983). Fuzzy numbers[J]. Journal of Mathematical Analysis and Applications. 92, 301e341.
Dündar, H., Ömürgönülşen, M., & Soysal, M. (2020). A review on sustainable urban vehicle routing. Journal of Cleaner Production, 125444.
Fakhrzad, M., Sadeghieh, A., Emami, L., (2012), A new multi-objective job shop scheduling with setup times using a hybrid genetic algorithm, International Journal of Engineering-Transactions B: Applications 26 (2): 207-218.
Fakhrzad, M.,Sadri Esfahani, 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.
Fraley, S., Oom, M., Terrien, B. and Date, J. (2006), Design of Experiments via Taguchi Methods: Orthogonal Arrays: The Michigan Chemical Process Dynamic and Controls, Open Text Book, USA
Gaur, J., Amini, M., & Rao, A. K. (2020). The impact of supply chain disruption on the closed-loop supply chain configuration profit: a study of sourcing policies. International Journal of Production Research, 58(17), 5380-5400.
Ghomi-Avili, M., Naeini, S. G. J., Tavakkoli-Moghaddam, R., & Jabbarzadeh, A. (2018). A fuzzy pricing model for a green competitive closed-loop supply chain network design in the presence of disruptions. Journal of Cleaner Production, 188, 425-442.
Gitinavard H, Akbarpour Shirazi M, Ghodsypour SH (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
Gitinavard, H., Akbarpour Shirazi, M., Fazel Zarandi, M. (2021). A possibilistic programming approach for biomass supply chain network design under hesitant fuzzy membership function estimation. Scientia Iranica
Gitinavard, H., Shirazi, M. A., & Zarandi, M. H. F. (2020). Sustainable feedstocks selection and renewable products allocation: A new hybrid adaptive utility-based consensus model. Journal of environmental management, 264, 110428.
Goli, A., Zare, H. K., Tavakkoli‐Moghaddam, R., & Sadegheih, A. (2020). A Multi-objective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment. Computational Intelligence, 36(1), 4-34.
Govindan, K., Mina, H., Esmaeili, A., & Gholami-Zanjani, S. M. (2020). An integrated hybrid approach for circular supplier selection and closed loop supply chain network design under uncertainty. Journal of Cleaner Production, 242, 118317.
Habibi, F., Barzinpour, F., Sadjadi, S. (2017). A Multi-objective optimization model for project scheduling with time-varying resource requirements and capacities. Journal of Industrial and Systems Engineering, 10(special issue on scheduling), 92-118.
Hajiaghaei-Keshteli, M., & Fard, A. M. F. (2019). Sustainable closed-loop supply chain network design with discount supposition. Neural computing and applications, 31(9), 5343-5377.
Hanss, Michael (2005). Applied Fuzzy Arithmetic, An Introduction with Engineering Applications. 3-540-24201-5: Springer
Jabbarzadeh, A., Fahimnia, B., & Sabouhi, F. (2018). Resilient and sustainable supply chain design: sustainability analysis under disruption risks. International Journal of Production Research, 56(17), 5945-5968.
Kalantari Khalil Abad, A., Pasandideh, S. (2020). A Multi-Objective Model for Green Closed-Loop Supply Chain Design by Handling Uncertainties inEffective Parameters. Journal of Quality Engineering and Production Optimization, 5(1), 221-242. doi: 10.22070/jqepo.2020.5398.1153
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. doi: 10.22070/jqepo.2021.14668.1192
Lai, Y.J., Hwang, C.L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy Sets Syst. 49(2), 121–133
Laumanns, M., Thiele, L., Zitzler, E. (2006). An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method. European Journal of Operational Research, 169(3), 932-942
Liang, T.F. (2006). Distribution planning decisions using interactive fuzzy multi-objective linear programming. Fuzzy Sets Syst. 157(10), 1303–1316
Lqbal, M. W., Kang, Y., & Jeon, H. W. (2020). Zero waste strategy for green supply chain management with minimization of energy consumption. Journal of Cleaner Production, 245, 118827.
Luis J.Zeballos, Carlos A. Mendez, Ana P. Barbosa-Povoa, (2018). Integrating decisions of product and closed-loop supply chain design under uncertain return flows. Computers & Chemical Engineering, 112, 211-238.
Malik, M. Z., Kumar, M., Soomro, A. M., Baloch, M. H., Gul, M., Farhan, M., & Kaloi, G. S. (2020). Strategic planning of renewable distributed generation in radial distribution system using advanced MOPSO method. Energy Reports, 6, 2872-2886.
Mamaghani, E. J., & Davari, S. (2020). The bi-objective periodic closed loop network design problem. Expert Systems with Applications, 144, 113068.
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 Cleaner Production, 242, 118452.
Moore. J, Chapman. R (1999). Application of particle swarm to multiobjective optimization, Department of Computer Science and Software Engineering, Auburn University
Nasr, A. K., Tavana, M., Alavi, B., & Mina, H. (2021). A novel fuzzy multi-objective circular supplier selection and order allocation model for sustainable closed-loop supply chains. Journal of Cleaner Production, 287, 124994.
Peng, H., Shen, N., Liao, H., Xue, H., & Wang, Q. (2020). Uncertainty factors, methods, and solutions of the closed-loop supply chain—A review of the current situation and future prospects. Journal of Cleaner Production, 254, 120032.
Rabbani .M, Oladzad-Abbasabady, N.(2022) Ambulance routing in disaster response considering variable patient condition: NSGA-II and MOPSO algorithms. Journal of Industrial and Management Optimization, 2022, 18 (2). 1035-1062
Rabbani, M., Hosseini-Mokhallesun, S. A. A., Ordibazar, A. H., & Farrokhi-Asl, H. (2020). A hybrid robust possibilistic approach for a sustainable supply chain location-allocation network design. International Journal of Systems Science: Operations & Logistics, 7(1), 60-75.
Rad, R. S., & Nahavandi, N. (2018). A novel multi-objective optimization model for the integrated problem of green closed loop supply chain network design and quantity discount. Journal of cleaner production, 196, 1549-1565.
Rahimi, M., & Ghezavati, V. (2018). Sustainable multi-period reverse logistics network design and planning under uncertainty utilizing conditional value at risk (CVaR) for recycling construction and demolition waste. Journal of Cleaner Production, 172, 1567-1581.
Reyhani, H., Jabarzadeh, Y., Ghaffarinasab, N., Kumar, V., Garza-Reyes, J.A. (2020). A multi-objective linear optimization model for designing a sustainable closed-loop agricultural supply chain. Proceedings of the 10th Conference on Industrial Engineering and Operations Management Dubai, UAE, 10-12 March, Michigan, USA: IEOM, pp. 1-12
Sadeghi Ahangar, S., Sadati, A., & Rabbani, M. (2021). Sustainable design of a municipal solid waste management system in an integrated closed-loop supply chain network using a fuzzy approach: a case study. Journal of Industrial and Production Engineering, 38(5), 323-340.
Tan, Y. F., & Cao, B. Y. (2005). Another discussion about the optimal solution to fuzzy constraints linear programming. In International Conference on Fuzzy Systems and Knowledge Discovery (pp. 156-159). Springer, Berlin, Heidelberg.
Vakili, R., Akbarpour Shirazi, M., & Gitinavard, H. (2020). Multi-echelon green open-location-routing problem: A robust-based stochastic optimization approach. Scientia Iranica.
Wang, G., & Gunasekaran, A. (2017). Operations scheduling in reverse supply chains: Identical demand and delivery deadlines. International Journal of Production Economics, 183, 375-381.
Wang, J., Jiang, H., & Yu, M. (2020). Pricing decisions in a dual-channel green supply chain with product customization. Journal of Cleaner Production, 247, 119101.
Wang, P., Huang, J., Cui, Z., Xie, L., & Chen, J. (2020). A Gaussian error correction multi‐objective positioning model with NSGA‐II. Concurrency and Computation: Practice and Experience, 32(5), e5464.
Wang, R.C., Liang, T.F. (2005). Applying possibilistic linear programming to aggregate production planning. Int. J. Prod. Econ. 98(3), 328–341
Yigit Kazancoglu, Damla Yuksel, Muruvvet Deniz Sezer, Sachin Kumar Mangla, Lianlian Hua,(2022), A Green Dual-Channel Closed-Loop Supply Chain Network Design Model, Journal of Cleaner Production, Volume 332, 130062
Yun, Y., Chuluunsukh, A., & Gen, M. (2020). Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach. Mathematics, 8(1), 84.
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