[1] Anderson, T. R., Hawkins, E., & Jones, P. D. (2016). CO2, the greenhouse effect and global warming: From the pioneering work of Arrhenius and Callendar to today’s earth system models. Endeavour, 40(3), 178–187. https://doi.org/10.1016/j.endeavour.2016.07.002
[2] Jauhari, W. A., Cahaya Sakti, C. T., Hisjam, M., & Hishamuddin, H. (2025). A sustainable circular economic supply chain model with green production, delays in payment, and Carbon tax regulation. Journal of cleaner production, 495, 145008. https://doi.org/10.1016/j.jclepro.2025.145008
[3] Lamb, W. F., Wiedmann, T., Pongratz, J., Andrew, R., Crippa, M., Olivier, J. G. J., Wiedenhofer, D., Mattioli, G., Al Khourdajie1, A., House, J., Pachauri, S., A Figueroa, M., Saheb, M., Slade, R., Hubacek, K., Sun, L., Kahn Ribeiro, S., Khennas, S., De La Rue Du Can, S., Chapungu, L., J Davis, S., Bashmakov, I., Dai, H., Dhakal, SH., Tan, X., Geng, Y., Gu, B., & Minx, J. (2021). A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018. Environmental research letters, 16(7), 73005. https://doi.org/10.1088/1748-9326/ABEE4E
[4] Amiri, M., & Bayatzadeh, S. (2025). Identifying and ranking digital solutions for managing supply chain disruptions (Case study: Steel industry). Modern research in performance evaluation, 3(4), 240–253. https://doi.org/10.22105/mrpe.2025.499771.1137
[5] Leung, D. Y. C., Caramanna, G., & Maroto-Valer, M. M. (2014). An overview of current status of Carbon Dioxide capture and storage technologies. Renewable and sustainable energy reviews, 39, 426–443. https://doi.org/10.1016/J.RSER.2014.07.093
[6] Min, H., & Kim, I. (2012). Green supply chain research: Past, present, and future. Logistics research, 4, 39–47. https://doi.org/10.1007/s12159-012-0071-3
[7] Saadati, H., & Hakimi, A. (2024). Optimizing the ticket response process in customer support systems using data-driven and machine learning methods: A Case study of IFDA. Optimality, 1(2), 188–204. https://doi.org/0.22105/opt.v1i2.57
[8] Tseng, M. L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Undefined, 141, 145–162. https://doi.org/10.1016/J.RESCONREC.2018.10.009
[9] Aldrighetti, R., Battini, D., Ivanov, D., & Zennaro, I. (2021). Costs of resilience and disruptions in supply chain network design models: A review and future research directions. International journal of production economics, 235, 108103. https://doi.org/10.1016/J.IJPE.2021.108103
[10] Ekram Nosratian, N., & Taghavi Fard, M. T. (2023). A proposed model for the assessment of supply chain management using DEA and knowledge management. Computational algorithms and numerical dimensions, 2(3), 136–147. https://doi.org/10.22105/cand.2023.191008
[11] Edalatpanah, S. A., Komazec, N., & Pamucar, D. (2024). Making two-channel pricing decisions in a multi-objective closed-loop supply chain network under uncertainty considering reliability (Case study: Steel industry). Big data and computing visions, 4(3), 201–218.
[12] Letafat, F., Gholamian, M. R., & Arabi, M. (2024). Designing a reliable supply chain network for perishable crops considering the risk of disruption (Case study: Tomato supply chain). Journal of decisions and operations research, 9(3), 666–689. https://doi.org/10.22105/dmor.2024.419272.1797
[13] ValizadehDizaj, Z., Fazlzadeh, A., Ahmadian, V., & Nagdi, S. (2025). Investigating the role of dynamic capability and supply chain resilience on companies' financial performance during disruptions. Innovation management and operational strategies. https://doi.org/10.22105/imos.2025.501248.1429
[14] Carter, C. R., & Liane Easton, P. (2011). Sustainable supply chain management: Evolution and future directions. International journal of physical distribution & logistics management, 41(1), 46–62. https://doi.org/10.1108/09600031111101420
[15] Rakshit, I. (2025). AI-driven cloud solutions for smart city data analytics. Systemic analytics, 3(1), 27–34. https://doi.org/10.31181/sa31202540
[16] Nagurney, A., Liu, Z., & Woolley, T. (2007). Sustainable supply chain and transportation networks. International journal of sustainable transportation, 1(1), 29–51. https://doi.org/10.1080/15568310601060077
[17] Sazvar, Z., Sepehri, M., & Baboli, A. (2016). A multi-objective multi-supplier sustainable supply chain with deteriorating products, case of cut flowers. IFAC-papersonline, 49(12), 1638–1643. https://doi.org/10.1016/j.ifacol.2016.07.815
[18] Fahimnia, B., Sarkis, J., & Eshragh, A. (2015). A tradeoff model for green supply chain planning: A leanness-versus-greenness analysis. Omega (United Kingdom), 54, 173–190. https://doi.org/10.1016/J.OMEGA.2015.01.014
[19] Mirzapour Al-e-hashem, S. M. J., Baboli, A., & Sazvar, Z. (2013). A stochastic aggregate production planning model in a green supply chain: Considering flexible lead times, nonlinear purchase and shortage cost functions. European journal of operational research, 230(1), 26–41. https://doi.org/10.1016/j.ejor.2013.03.033
[20] Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2012). Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy sets and systems, 206, 1–20. 10.1016/j.fss.2012.04.010
[21] 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, 260, 120842. https://doi.org/10.1016/j.jclepro.2020.120842
[22] Gholizadeh, H., & Fazlollahtabar, H. (2020). Robust optimization and modified genetic algorithm for a closed loop green supply chain under uncertainty: Case study in melting industry. Computers & industrial engineering, 147, 106653. https://doi.org/10.1016/j.cie.2020.106653
[23] 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. 297-314 . https://doi.org/10.1016/j.jclepro.2015.02.075
[24] Wang, J., & Wan, Q. (2022). A multi-period multi-product green supply network design problem with price and greenness dependent demands under uncertainty. Applied soft computing, 114, 108078. https://doi.org/10.1016/j.asoc.2021.108078
[25] Golpîra, H., & Javanmardan, A. (2022). Robust optimization of sustainable closed-loop supply chain considering carbon emission schemes. Sustainable production and consumption, 30, 640–656. https://doi.org/10.1016/j.spc.2021.12.028
[26] Sadeghi Rad, R., & Nahavandi, N. (2018). A novel multi-objective optimization model for integrated problem of green closed loop supply chain network design and quantity discount. Journal of cleaner production, 196, 1549–1565. https://doi.org/10.1016/j.jclepro.2018.06.034