The sustainable supply chain of CO2 emissions during the coronavirus disease (COVID-19) pandemic
محورهای موضوعی : Mathematical Optimization
sina abbasi
1
,
Maryam Daneshmand-Mehr
2
,
Armin Ghane Kanafi
3
1 - Department of Industrial Engineering,
Lahijan branch, Islamic Azad University, Lahijan, IRAN
2 - Department of Industrial Engineering, Islamic Azad University of Lahijan, Lahijan, Gilan, Iran.
3 - Department O mathematics, Islamic Azad University of Lahijan, Lahijan, Iran
کلید واژه: Sustainability, Covid-19 pandemic, Closed-loop Supply Chain Network, Lockdowns, Multi-objective Mixed-Integer Programming,
چکیده مقاله :
This investigation aims to demonstrate an application mathematical model of the sustainable closed-loop supply chain network (SCLSCN) during the COVID-19 pandemic. The suggested model can illustrate the trade-offs between environmental, economic, and social dimensions during the epidemic. The costs include the normal costs and the hygienic costs. The total cost was increased in the COVID-19 pandemic by 25.14 %. The novelty social aspects of this model include the average number of lost days caused by COVID-19 damage and the number of created new job opportunities related to COVID-19. The average number of lost days caused by damages increased by 51.64 % during COVID-19. The CO2 emissions were decreased by17.42 %. This paper presents a multi-objective mixed-integer programming (MOMIP) problem. We use the weighted sum method (WSM) approach for the scalarization approach. To optimize the process, Lingo software has been used. Our contributions to this research are i) Suggested an application model of SSC to show better the trade-offs between three aspects of sustainability in the COVID-19 pandemic and lockdown periods, ii) Designing the hygienic and safe SC for employees, iii) developing the social and economic indicators, iv) We have found the negative and positive impacts of COVID-19 and lockdowns on SC, v) Finally, we analyze the mathematical model and discuss managerial implications. Therefore, this investigation tries to fill this gap for COVID-19 condition disaster. This research's novelty is to simultaneously present a MOMIP model, COVID-19 issues, and hygienic rules, in a closed-loop supply chain (CLSC) framework.
[1] Klemeš, J. J., Van Fan, Y., & Jiang, P. (2020). The energy and environmental footprints of COVID-19 fighting measures–PPE, disinfection, supply chains. Energy, 211, 118701.
[2] Sodhi, M. S., & Tang, C. S. (2021). Supply chain management for extreme conditions: research opportunities. Journal of Supply Chain Management, 57(1), 7-16.
[3] de Sousa Jabbour, A. B. L., Jabbour, C. J. C., Hingley, M., VilaltaPerdomo, E. L., Ramsden, G., & Twigg, D. (2020). Sustainability of supply chains in the wake of the coronavirus (COVID-19/SARS-CoV-2) pandemic: lessons and trends. Modern Supply Chain Research and Applications.
[4] Guidance Protocol for personal hygiene due to ongoing measures related to COVID-19 scenario, Copyright © CEMEX Innovation Holding AG. (2020). This protocol was prepared by CEMEX based on the recommendations of the World Health Organization (" WHO "), external
consultants, and the experience of the company itself.
[5] Ivanov, D., & Das, A. (2020). Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: A research note. International Journal of Integrated Supply Management, 13(1), 90-102.
[6] Rowan, N. J., & Laffey, J. G. (2020). Challenges and solutions for addressing critical shortage of supply chain for personal and protective equipment (PPE) arising from Coronavirus disease (COVID19) pandemic– Case study from the Republic of Ireland. Science of the Total
Environment, 725, 138532.
[7] Ivanov. D. (2020). “Predicting the impacts of epidemic outbreaks on global supply chains: a simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case”, Shipping Research Part E: Logistics and Shipping Review, Vol. 136, p. 101922.
[8] Jill E. Hobbs. (2020). Food supply chains during the COVID-19 pandemic, SPECIAL ISSUE ARTICLE. Department of Agricultural and Resource Economics, University of Saskatchewan, Canada, DOI10.1111/cjag.12237
[9] Tsiakis, P., Shah, N., & Pantelides, C. C. (2001). Design of multi-echelon supply chain networks under demand uncertainty. Industrial & engineering chemistry research, 40(16), 3585-3604.
[10] Azadi, M., Jafarian, M., Saen, R. F., & Mirhedayatian, S. M. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers & Operations Research, 54, 274-285.
[11] Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. International Journal of Production Research, 58(10), 2904-2915.
[12] FREE, C., & HECIMOVIC, A. (2021). GLOBAL SUPPLY CHAINS AFTER COVID-19: THE END OF THE ROAD FOR NEOLIBERAL GLOBALISATION? ACCOUNTING, AUDITING & ACCOUNTABILITY JOURNAL. [13] ILLAHI, U., & MIR, M. S. (2021). MAINTAINING EFFICIENT LOGISTICS AND SUPPLY CHAIN MANAGEMENT OPERATIONS DURING AND AFTER CORONAVIRUS (COVID-19) PANDEMIC: LEARNING FROM THE PAST EXPERIENCES. ENVIRONMENT, DEVELOPMENT AND SUSTAINABILITY, 23(8), 11157-11178.
[14] Nandi, S., Sarkis, J., Hervani, A. A., & Helms, M. M. (2021). Redesigning supply chains using blockchain-enabled circular economy and COVID-19 experiences. Sustainable Production and Consumption, 27, 10-22.
[15] Shahed, K. S., Azeem, A., Ali, S. M., & Moktadir, M. (2021). A supply chain disruption risk mitigation model to manage COVID-19 pandemic risk. Environmental Science and Pollution Research, 1-16.
[16] GÜNER, H. R., Hasanoğlu, İ., & Aktaş, F. (2020). COVID-19: Prevention and control measures in community. Turkish Journal of medical sciences, 50(SI-1), 571-577.
[17] Wang, R., Xiong, Y., Xing, X., Yang, R., Li, J., Wang, Y., ... & Tao, S. (2020). Daily CO2 emission reduction indicates the control of activities to contain COVID-19 in China. The Innovation, 1(3), 100062.
[18] Edward, R. (2020). An overview of the rapid test situation for COVID19 diagnosis in the EU/EEA.
[19] Matthias Ehrgott. (2005). Multicriteria Optimization, spring berlin. Heidelberg, printed in Germany.
[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.
[21] Zakeri, A., Dehghanian, F., Fahimnia, B., & Sarkis, J. (2015). Carbon pricing versus emissions trading: A supply chain planning perspective. International Journal of Production Economics, 164, 197-205.
[22] Mohammed, F., Selim, S. Z., Hassan, A., & Syed, M. N. (2017). Multiperiod planning of closed-loop supply chain with carbon policies under uncertainty. Transportation Research Part D: Transport and Environment, 51, 146-172.
[23] Xu, Z., Pokharel, S., Elomri, A., & Mutlu, F. (2017). Emission policies and their analysis for the design of hybrid and dedicated closed-loop supply chains. Journal of cleaner production, 142, 4152-4168.
[24] FAROOQ, M. U., HUSSAIN, A., MASOOD, T., & HABIB, M. S. (2021). SUPPLY CHAIN OPERATIONS MANAGEMENT IN PANDEMICS: A STATE-OF-THEART REVIEW INSPIRED BY COVID-19. SUSTAINABILITY, 13(5), 2504
[25] Paksoy, T., Bektas, T., & Özceylan, E. (2011). Operational and environmental performance measures in a multi-product closed-loop supply chain. Transportation Research Part E: Logistics and Transportation Review, 47(4), 532-546.
[26] Končar, J., Grubor, A., Marić, R., Vučenović, S., & Vukmirović, G. (2020). Setbacks to IoT implementation in the function of FMCG supply chain sustainability during COVID-19 pandemic. Sustainability, 12(18), 7391.
[27] Chiu, C. Y., Cheng, C. Y., & Wu, T. Y. (2021). Integrated Operational Model of Green Closed- Loop Supply Chain. Sustainability, 13(11), 6041.
[28]: Altiparmak, F., Gen, M., Lin, L., Paksoy, T.A.) 2006.( Genetic algorithm approach for multi-objective optimization of supply chain networks. Comput. Ind. Eng. 51 (1), 196–215, Special Issue on Computational Intelligence and Information Technology: Applications to Industrial Engineering 33rd. ICC&IE – Computational Intelligence & Information.
[29] Waltho, C. (2019). Green Supply Chain Network Design with Emission Sensitive Demand.
[30] Fareeduddin, M., Hassan, A., Syed, M. N., & Selim, S. Z. (2015). The impact of carbon policies on closed-loop supply chain network design. Procedia CIRP, 26, 335-340.
[31] Myllyvirta, L. (2020). Coronavirus temporarily reduced China’s CO 2 emissions by a quarter. Carbon Brief.
[32] Avoiding unnecessary travel, Emerald Group, (2021).
[33] Martí, J. M. C., Tancrez, J. S., & Seifert, R. W. (2015). Carbon footprint and responsiveness trade-offs in supply chain network design. International Journal of Production Economics, 166, 129-142.
[34] Yachai, K., Kongboon, R., Gheewala, S. H., & Sampattagul, S. (2021). Carbon footprint adaptation on green supply chain and logistics of papaya in Yasothon Province using geographic information system. Journal of Cleaner Production, 281, 125214.
[35] 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.
[36] Somani, M., Srivastava, A. N., Gummadivalli, S. K., & Sharma, A. (2020). Indirect implications of COVID-19 towards sustainable environment: an investigation in Indian context. Bioresource Technology Reports, 11, 100491.
[37] Lang, L., Liu, Z., & Hu, B. (2021, February). Optimization decision of cooperative emission reduction of clothing supply chain based on carbon tax. In Journal of Physics: Conference Series (Vol. 1790, No. 1, p. 012092). IOP Publishing.
[38] Benjaafar, S., Li, Y., & Daskin, M. (2012). Carbon footprint and the management of supply chains: Insights from simple models. IEEE transactions on automation science and engineering, 10(1), 99-116.
[39] Zhang, G., Sun, H., Hu, J., & Dai, G. (2014). The closed-loop supply chain network equilibrium with products lifetime and carbon emission constraints in multiperiod planning horizon. Discrete Dynamics in Nature and Society, 2014.
[40] Hammami, R., Nouira, I., & Frein, Y. (2015). Carbon emissions in a multi-echelon production-inventory model with lead time constraints. International Journal of Production Economics, 164, 292-307.
[41] Tao, Z. G., Guang, Z. Y., Hao, S., & Song, H. J. (2015). Multi-period closed-loop supply chain network equilibrium with carbon emission constraints. Resources, Conservation and Recycling, 104, 354-365.
[42] Zhou, Y., Gong, D. C., Huang, B., & Peters, B. A. (2015). The impacts of carbon tariff on green supply chain design. IEEE Transactions on Automation Science and Engineering, 14(3), 1542-1555.
[43] Diabat, A., Abdallah, T., Al-Refaie, A., Svetinovic, D., & Govindan, K. (2012). Strategic closed-loop facility location problem with carbon market trading. IEEE Transactions on engineering Management, 60(2), 398-408
[44] Nationalgeographic.com
[45] Rezaee, A., Dehghanian, F., Fahimnia, B., & Beamon, B. (2017). Green supply chain network design with stochastic demand and carbon price. Annals of operations research, 250(2), 463-485.
[46] Global Climate report. (2019). Available at. https://www.ncdc.noaa.gov/sotc/global/201913.
[47] Scientific Americans. (2020).
[48] Choudhary, A., Sarkar, S., Settur, S., & Tiwari, M. K. (2015). A carbon market sensitive optimization model for integrated forward–reverse logistics. International Journal of Production Economics, 164, 433-444.
[49] ABDALLAH, T., DIABAT, A., & RIGTER, J. (2013). INVESTIGATING THE OPTION OF INSTALLING SMALL SCALE PVS ON FACILITY ROOFTOPS IN A GREEN SUPPLY CHAIN. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 146(2), 465-477.
[50] Cai, Q., Ma, L., Gong, M., & Tian, D. (2016). A survey on network community detection based on evolutionary computation. International Journal of Bio-Inspired Computation, 8(2), 84-98.
[51] Mousavi, R., Salehi-Amiri, A., Zahedi, A., & Hajiaghaei-Keshteli, M. (2021). Designing a supply chain network for blood decomposition by utilizing social and environmental factor. Computers & Industrial Engineering, 160, 107501.
[52] Soleimani, H., Govindan, K., Saghafi, H., & Jafari, H. (2017). Fuzzy multi-objective sustainable and green closed-loop supply chain network design. Computers & industrial engineering, 109, 191-203.
[53] Yi, Y., & Li, J. (2018). Cost-sharing contracts for energy saving and emissions reduction of a supply chain under the conditions of government subsidies and a carbon tax. Sustainability, 10(3), 895.
[54] Mosallanezhad, B., Chouhan, V. K., Paydar, M. M., & HajiaghaeiKeshteli, M. (2021). Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic. Applied Soft Computing, 112, 107809.
[55] Zahedi, A., Salehi-Amiri, A., Smith, N. R., & Hajiaghaei-Keshteli, M. (2021). Utilizing IoT to design a relief supply chain network for the SARSCOV-2 pandemic. Applied Soft Computing, 104, 107210.
[56] Goodarzian, F., Taleizadeh, A. A., Ghasemi, P., & Abraham, A. (2021). An integrated sustainable medical supply chain network during COVID19. Engineering Applications of Artificial Intelligence, 100, 104188.
[57] Shirazi, H., Kia, R., & Ghasemi, P. (2021). A stochastic bi-objective simulation–optimization model for plasma supply chain in case of COVID-19 outbreak. Applied Soft Computing, 112, 107725.
[58] Goodarzian, F., Ghasemi, P., Gunasekaren, A., Taleizadeh, A. A., & Abraham, A. (2021). A sustainable-resilience healthcare network for handling COVID-19 pandemic. Annals of operations research, 1-65.
[59] Ghasemi, P., Goodarzian, F., Gunasekaran, A., & Abraham, A. (2021). A bi-level mathematical model for logistic management considering the evolutionary game with environmental feedbacks. The International Journal of Logistics Management.
[60] Tirkolaee, E. B., Goli, A., Ghasemi, P., & Goodarzian, F. (2022). Designing a sustainable closed-loop supply chain network of face masks during the COVID-19 pandemic: Pareto-based algorithms. Journal of Cleaner Production, 333, 130056.
[61] Xu, L., Wang, C., & Zhao, J. (2018). Decision and coordination in the dual-channel supply chain considering cap-and-trade regulation. Journal of Cleaner Production, 197, 551-561.
[62] Li, X., Peng, Y., & Zhang, J. (2017). A mathematical/physics carbon emission reduction strategy for building supply chain network based on carbon tax policy. Open Physics, 15(1), 97-107.
[63] Shirazi, H., Kia, R., & Ghasemi, P. (2020). Ranking of hospitals in the case of COVID-19 outbreak: A new integrated approach using patient satisfaction criteria. International Journal of Healthcare Management, 13(4), 312-324.
[64] Rume, T., & Islam, S. D. U. (2020). Environmental effects of COVID19 pandemic and potential strategies of sustainability. Heliyon, 6(9), e04965.
[65]: Selvaranjan, K., Navaratnam, S., Rajeev, P., & Ravintherakumaran, N. (2021). Environmental challenges induced by extensive use of face masks during COVID-19: A review and potential solutions. Environmental Challenges, 3, 100039.
[66]: Anser, M. K., Yousaf, Z., Khan, M. A., Voo, X. H., Nassani, A. A., Alotaibi, S. M., ... & Zaman, K. (2020). The impacts of COVID-19 measures on global environment and fertility rate: double coincidence. Air Quality, Atmosphere & Health, 13(9), 1083-1092.
[67]: Bilal, Bashir, M. F., Benghoul, M., Numan, U., Shakoor, A., Komal, B., Bashir, M. A., Bashir, M., & Tan, D. (2020). Environmental pollution and COVID-19 outbreak: insights from Germany. Air quality, atmosphere, & health, 1–10. Advance online publication. https://doi.org/10.1007/s11869-
020-00893-9
[68]: Cheval, S., Mihai Adamescu, C., Georgiadis, T., Herrnegger, M., Piticar, A., & Legates, D. R. (2020). Observed and potential impacts of the COVID19 pandemic on the environment. International journal of environmental research and public health, 17(11), 4140.
[69]: Saadat, S., Rawtani, D., & Hussain, C. M. (2020). Environmental perspective of COVID-19. Science of the Total environment, 728, 138870.
[70]: SanJuan-Reyes, S., Gómez-Oliván, L. M., & Islas-Flores, H. (2021). COVID-19 in the environment. Chemosphere, 263, 127973.
[71]: Zambrano-Monserrate, M. A., Ruano, M. A., & Sanchez-Alcalde, L (2020). Indirect effects of COVID-19 on the environment. Science of the total environment, 728, 138813.
[72]: Malliet, P., Reynès, F., Landa, G., Hamdi-Cherif, M., & Saussay, A. (2020). Assessing short-term and long-term economic and environmental effects of the COVID-19 crisis in France. Environmental and Resource Economics, 76(4), 867-883.
[73]: Barreiro-Gen, M., Lozano, R., & Zafar, A. (2020). Changes in sustainability priorities in Organisations due to the COVID-19 outbreak: averting environmental rebound effects on society. Sustainability, 12(12), 5031.
[74] Emmerich, M., & Deutz, A. H. (2018). A tutorial on multi-objective optimization: fundamentals and evolutionary methods. Natural computing, 17(3), 585-609.
[75] Kannan, D., Diabat, A., Alrefaei, M., Govindan, K., & Yong, G. (2012). A carbon footprint based reverse logistics network design model. Resources, conservation and recycling, 67, 75-79.
[76] Broomandi, P., Karaca, F., Nikfal, A., Jahanbakhshi, A., Tamjidi, M., & Kim, J. R. (2020). Impact of COVID-19 event on the air quality in Iran. Aerosol and Air Quality Research, 20(8), 1793-1804.
[77] He, F., Deng, Y., & Li, W. (2020). Coronavirus disease 2019: What we know? Journal of medical virology, 92(7), 719-725.
[78] Kilpatrick, J., & Barter, L. (2020). COVID-19: managing supply chain risk and disruption. Deloitte: Toronto, ON, Canada.
[79] Ghadami, N., Gheibi, M., Kian, Z., Faramarz, M. G., Naghedi, R., Eftekhari, M., ... & Tian, G. (2021). Implementation of solar energy in smart cities using an integration of artificial neural network, photovoltaic system and classical Delphi methods. Sustainable Cities and Society, 74, 103149.
[80] Chen, J., Wang, H., & Fu, Y. (2022). A multi-stage supply chain disruption mitigation strategy considering product life cycle during COVID19. Environmental Science and Pollution Research, 1-15.
[81] Hosseini, S. M., Paydar, M. M., & Hajiaghaei-Keshteli, M. (2021). Recovery solutions for ecotourism centers during the Covid-19 pandemic: Utilizing Fuzzy DEMATEL and Fuzzy VIKOR methods. Expert Systems with Applications, 185, 115594.
[82] Huge-Brodin, M., Sweeney, E., & Evangelista, P. (2020). Environmental alignment between logistics service providers and shippers– a supply chain perspective. The International Journal of Logistics Management.
[85] Raj, A., Mukherjee, A. A., de Sousa Jabbour, A. B. L., & Srivastava, S. K. (2022). Supply Chain Management during and post-COVID-19 Pandemic: Mitigation Strategies and Practical Lessons Learned. Journal of Business Research.
[83] Quan, J., Wang, X., Wang, X., Xia, D., & Yang, J. B. (2021). Performance optimization of supply chain based on cooperative contract with disappointment-aversion strategic consumers. Flexible Services and Manufacturing Journal, 1-21.
[84] Ferretti, I., Zanoni, S., Zavanella, L., & Diana, A. (2007). Greening the aluminum supply chain. International Journal of Production Economics, 108(1-2), 236-245.
[85] Wang, F., Lai, X., & Shi, N. (2011). A multi-objective optimization for green supply chain network design. Decision support systems, 51(2), 262-269.
[86] Pozo, C., Ruz-Femenia, R., Caballero, J., Guilln-Goslbez, G., Jimnez, L., 2012. On the use of principal component analysis for reducing the number of environmental objectives in multi-objective optimization: application to the design of chemical supply chains. Chem. Eng. Sci. 69 (1), 146–158.
[87] Golini, R., & Kalchschmidt, M. G. M. (2011). Sustainability in the food supply chain: evidences from the Italian beef industry. In 22th Annual POMS Conference.
[88] Sabio, N., Kostin, A., Guilln-Goslbez, G., Jimnez, L., 2012. Holistic minimization of the life cycles environmental impact of hydrogen infrastructures using multi-objective optimization and principal component analysis. Int. J. Hydrog. Energy 37(6), 5385–5405, Optimization Approaches
to Hydrogen Logistics.
[89] Zhang, C.-T., Liu, L.-P., 2013. Research on coordination mechanism in three-level green supply chain under non-cooperative game. Appl. Math. Model. 37 (5), 3369–3379.
[90] Al-Othman. W. B, Lababidi. H.M, Alatiqi. I.M., Al-Shayji, K. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. Eur. J. Oper. Res, ,189 (3), 822–840
[91] Ozkir, V., Basligil, H., 2013. Multi-objective optimization of closedloop supply chains in uncertain environment. J. Clean. Prod. 41 (0), 114–125.
[92] Devika, K., Jafarian, A., & Nourbakhsh, V. (2014). Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques. European Journal of Operational Research, 235(3), 594-615.
[93] Zhang, H., & Yang, K. (2020). Multi-objective optimization for green dual-channel supply chain network design considering transportation mode selection. In Supply Chain and Logistics Management: Concepts, Methodologies, Tools, and Applications (pp. 382-404). IGI Global.
[94] Barzinpour, F., & Taki, P. (2018). A dual-channel network design model in a green supply chain considering pricing and transportation mode choice. Journal of Intelligent Manufacturing, 29(7), 1465-1483.
[95] Jamshidi, R., Ghomi, S. F., & Karimi, B. (2012). Multi-objective green supply chain optimization with a new hybrid memetic algorithm using the Taguchi method. Scientia Iranica, 19(6), 1876-1886
[96] Chen, C., Zhang, G., & Xia, Y. (2019). Remanufacturing network design for the dual-channel closed-loop supply chain. Procedia CIRP, 83, 479-484.
[97] Mohebalizadehgashti, F., Zolfagharinia, H., & Amin, S. H. (2020). Designing a green meat supply chain network: A multi-objective approach. International Journal of Production Economics, 219, 312-327.
[98] Li, J., Fang, Y., & Yang, J. (2022). Minimizing carbon emissions of the rice supply chain considering the size of deep tillage lands. Sustainable Production and Consumption, 29, 744-760.
[99] Theophilus O, Dulebenets MA, Pasha J, Lau YY, Fathollahi-Fard AM, Mazaheri A (2021) Truck scheduling optimization at a cold-chain crossdocking terminal with product perishability considerations. Comput Ind Eng 156:107240.
[100] Hajiaghaei-Keshteli, M., & Fathollahi Fard, A. M. (2019). Sustainable closed-loop supply chain network design with discount supposition. Neural computing and applications, 31(9), 5343-5377.
[101] Khorshidvand, B., Soleimani, H., Sibdari, S., & Esfahan, M. M. S. (2021). A hybrid modeling approach for green and sustainable closed-loop supply chain considering price, advertisement and uncertain demands. Computers & Industrial Engineering, 157, 107326.
[102] Fasihi, M., Tavakkoli-Moghaddam, R., Najafi, S. E., & HajiaghaeiKeshteli, M. (2021). Developing a Bi-objective Mathematical Model to Design the Fish Closed-loop Supply Chain. International Journal of Engineering, 34(5), 1257-1268.
[103] Goodarzian, F., Taleizadeh, A. A., Ghasemi, P., & Abraham, A. (2021). An integrated sustainable medical supply chain network during COVID-19. Engineering Applications of Artificial Intelligence, 100, 104188.
[104] Mayanti, B., & Helo, P. (2022). Closed-loop supply [chain potential of agricultural plastic waste: Economic and environmental assessment of bale wrap waste recycling in Finland. International Journal of Production Economics, 244, 108347.
[105] Salehi-Amiri A, Zahedi A, Akbapour N, Hajiaghaei-Keshteli M (2021) Designing a sustainable closed-loop supply chain network for walnut industry. Renew Sust Energ Rev 141:110821
[106] Yang, D., Song, D., & Li, C. (2022). Environmental responsibility decisions of a supply chain under different channel leaderships. Environmental Technology & Innovation, 102212.
[107] Akbari-Kasgari, M., Khademi-Zare, H., Fakhrzad, M. B., HajiaghaeiKeshteli, M., & Honarvar, M. (2022). Designing a resilient and sustainable closed-loop supply chain network in copper industry. Clean Technologies and Environmental Policy, 1-28.
[108] Kazancoglu, Y., Yuksel, D., Sezer, M. D., Mangla, S. K., & Hua, L. (2022). A Green Dual-Channel Closed-Loop Supply Chain Network Design Model. Journal of Cleaner Production, 332, 130062.
[109] Ahmad, F., Alnowibet, K. A., Alrasheedi, A. F., & Adhami, A. Y. (2022). A multi-objective model for optimizing the socio-economic performance of a pharmaceutical supply chain. Socio-Economic Planning Sciences, 79, 101126.
[110] Nurjanni, K. P., Carvalho, M. S., & Costa, L. (2017). Green supply chain design: A mathematical modeling approach based on a multi-objective optimization model. International Journal of Production Economics, 183, 421-432.
[111] Sherafati, M., Bashiri, M., Tavakkoli-Moghaddam, R., & Pishvaee, M. S. (2019). Supply chain network design considering sustainable development paradigm: A case study in cable industry. Journal of Cleaner Production, 234, 366-380.
[112] Google Maps. (2022). https://www.google.com/maps/@7.2022,81.0753,12z
[113] Bera, B., Bhattacharjee, S., Shit, P. K., Sengupta, N., & Saha, S. (2021). Significant impacts of COVID-19 lockdown on urban air pollution in Kolkata (India) and amelioration of environmental health. Environment, development and sustainability, 23(5), 6913-6940.
[114] Heidelberg Cement Group (2020) & (2021). https://www.heidelbergcement.com/en
[115] Allaoui, H., Guo, Y., Choudhary, A., & Bloemhof, J. (2018). Sustainable agro-food supply chain design using two-stage hybrid multiobjective decision-making approach. Computers & Operations Research, 89, 369-384.
