A p-robust mathematical model for a sustainable vaccine supply chain
محورهای موضوعی : Supply Chain ManagementMahmoud Pormollaahmad 1 , Saeed Fazayeli 2 , Ali Doniavi 3
1 - Master of Science in engineering, Urmia University, Urmia, West Azerbaijan Province, Iran
2 - Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran
3 - Associate Professor, Department of Industrial Engineering, Urmia University, Urmia, Iran
کلید واژه: Words: vaccine supply Chain, sustainability, p-robust model,
چکیده مقاله :
This paper introduces a multi-product, multi-period, and multi-level sustainable supply chain (SC) network problem, including several production centers. It includes stocking technology and different transportation methods in conditions of uncertainty. The increasing demand for vaccines in the conditions of the corona virus epidemic and the existing sensitivities towards the stability characteristics as well as the unique characteristics of the vaccine SC are the reasons for redesigning this network. The economic, environmental and social goals are considered in presented mathematical model in order to achieve organization's sustainability strategy and stakeholder satisfaction. The economic objective function includes two types of tactical and strategic costs to avoid creating sub-optimal solutions. The environmental objective function calculates the total emission of pollution in SC. The social objective is to maximize the social responsiveness of the SC. Three indicators including job opportunity creation (positive effect), employee health and safety (negative effect) and customer health as risk of harm to customer using product (negative effect). LP metric and epsilon limit methods are used to solve the model in small dimensions and Pareto front drawing method is used to draw the conflict of interest diagram. A numerical example has been proposed to evaluate and test the model, and in order to deal with non-deterministic parameters and reduce its impact on the optimal solution, a robust optimization model has been proposed. Finally, the results in deterministic and robust state has been compared.
This paper introduces a multi-product, multi-period, and multi-level sustainable supply chain (SC) network problem, including several production centers. It includes stocking technology and different transportation methods in conditions of uncertainty. The increasing demand for vaccines in the conditions of the corona virus epidemic and the existing sensitivities towards the stability characteristics as well as the unique characteristics of the vaccine SC are the reasons for redesigning this network. The economic, environmental and social goals are considered in presented mathematical model in order to achieve organization's sustainability strategy and stakeholder satisfaction. The economic objective function includes two types of tactical and strategic costs to avoid creating sub-optimal solutions. The environmental objective function calculates the total emission of pollution in SC. The social objective is to maximize the social responsiveness of the SC. Three indicators including job opportunity creation (positive effect), employee health and safety (negative effect) and customer health as risk of harm to customer using product (negative effect). LP metric and epsilon limit methods are used to solve the model in small dimensions and Pareto front drawing method is used to draw the conflict of interest diagram. A numerical example has been proposed to evaluate and test the model, and in order to deal with non-deterministic parameters and reduce its impact on the optimal solution, a robust optimization model has been proposed. Finally, the results in deterministic and robust state has been compared.
[1] Aminifar Z., Arabi M. (2014) Sustainable supply chain management and the need to investigate it, International Conference on New Researches in Industrial Management and Engineering, Tehran.
[2] Nayeri S., Torabi A., Tavakoli M., Sazvar Z. (2021) A multi-objective fuzzy robust stochastic model for designing a sustainable-resilient-responsive supply chain network, Journal of Cleaner Production, 311, 126-691.
[3] Sazvar Z., Tafakkori k., Oladzad N., Nayeri S. (2021) A capacity planning approach for sustainable-resilient supply chain network design under uncertainty: A case study of vaccine supply chain, Computers & Industrial Engineering, 159, 107-406.
[4] Karmakar M., Lantz P. M., Tipirneni R. (2021) Association of Social and Demographic Factors With COVID-19 Incidence and Death Rates in the US, JAMA Netw Open. 4(1):e2036462. doi:10.1001/jamanetworkopen.2020.36462.
[5] P-Georgiadis G., C-Georgiadis A. (2021) Optimal planning of the COVID-19 vaccine supply chain, Volume 39, Issue 37, Pages 5302-5312. DOI: 10. 1016/j. vaccine. 2021. 07. 068.
[6] Y- Lee B., A-Haidari L. (2017) The importance of vaccine supply chains to everyone in the vaccine world, Journal of Vaccine, https: //doi. org/10. 1016/j. vaccine. 2017. 05. 096.
[7] Mofijur M., Fattah I. R., Alam M. A., Islam A. S., Ong H. C., Rahman S. A., Najafi G., Ahmed S. F., Uddin M. A., Mahlia T. M. I. (2021) Impact of COVID-19 on the social, economic, environmental and energy domains: lessons learnt from a global pandemic, Sustain. Prod. Consum, 26, 343–359.
[8] Ivanov D., Dolgui A. (2021) OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implica- tions. International Journal of Production Economics 232,107921.
[9] Gholipoor A., Paydar M. M., Safaei A. S. (2019) a faucet closed-loop supply chain network design considering used faucet exchange plan, J. Clean. Prod, 235, 503–518.
[10] Babazadeh R., Razmi J., Pishvaee M. S., Rabbani M. (2017) A sustainable second-generation biodiesel supply chain network design problem under risk, Omega (United Kingdom), 66, 258–277.
[11] Mousavi Ahranjani P., Ghaderi S. F., Azadeh A., Babazadeh R. (2018) Hybrid multiobjective robust possibilistic programming approach to a sustainable bioethanol sup ply chain network design, Ind. Eng. Chem. Res, 57, (44), 15066–15083.
[12] Zahiri B., Zhuang J., Mohammadi M. (2017) Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study, Journal of Transportation Research Part E, 103, 109-142.
[13] Eskandarpour M., Dejax P., Miemczyk J., Péton O. (2015) Sustainable supply chain network design: an optimization-oriented review, Omega, 54, 11–32.
[14] Habib M. S., Asghar O., Hussain A., Imran M., Mughal M. P., Sarkar B. (2021) A robust possibilistic programming approach toward animal fat-based biodiesel supply chain network design under uncertain environment, J. Clean. Prod. 122-403.
[15] Yu H., Solvang W. D. (2020) A fuzzy-stochastic multi-objective model for sustainable planning of a closed-loop supply chain considering mixed uncertainty and network flex- ibility, J. Clean. Prod. 266 121702.
[16] Shen J. (2020) An uncertain sustainable supply chain network, Appl. Math. Comput. 378, 125213.
[17] Sherafati M., Bashiri M., Tavakkoli-Moghaddam R., Pishvaee M. S. (2020) Achieving sustainable development of supply chain by incorporating various carbon reg- ulatory mechanisms, Transport. Res. Part D 102253.
[18] Mota B., Gomes M. I., carvalho A., Barbosa-Povoa A. P. (2018) Sustainable supply chains: A integrated modeling approach under uncertainty, Omega 77, 32–57.
[19] Mahmud P., Ahmed M., Janan F., Xames D., Chowdhury N.R. (2023) Strategies to develop a sustainable and resilient vaccine supply chain in the context of a developing economy, Socio-Economic Planning Sciences, 87, Part B.
[20] Gilani H., Sahebi H. (2023) A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain, Omega, Volume 110.
[21] Babaee Tirkolaee E., Ebadi Torkayesh E., Tavana M., Goli A., Simic V., Ding W. (2023) An integrated decision support framework for resilient vaccine supply chain network design, Engineering Applications of Artificial Intelligence, Volume 126, Part B.
[22] Gan Q., Zhang, Y. Zhang Z., Chen M., Zhao J., Wang X. (2023) Influencing factors of cooling performance of portable cold storage box for vaccine supply chain: An experimental study, Journal of Energy Storage, Volume 72, Part A.
[23] Khodaee V., Kayvanfar V., Haji A. (2022) A humanitarian cold supply chain distribution model with equity consideration: The case of COVID-19 vaccine distribution in the European Union, Decision Analytics Journal, Volume 4.
[24] Lin Q., Zhao Q., Lev B. (2020) Cold chain transportation decision in the vaccine supply chain, European Journal of Operational Research, Volume 283, Issue 1.
[25] Kumar S., Mvundura M., Ray A., Haldar P., Lennon P., Muller N., Roy A., Rewaria S (2023) Using new cold chain technologies to extend the vaccine cold chain in India: Equipment performance, acceptability, systems fit, and costs, Vaccine: X, Volume 15.
[26] Ahi P., Searcy C. (2014) an analysis of metrics used to measure performance in green and sustainable supply chains, Journal of Cleaner Production, 1-18.
[27] Ivo de Carvalho M., Ribeiro D., Paula Barbosa-Povoa A. (2019) Design and Planning of Sustainable Vaccine Supply Chain, DOI: 10. 1007/978-3-030-15398-4_2.
[28] 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.
[29] Vali-Siar M. M., Roghanian E. (2022) Sustainable, resilient and responsive mixed supply chain network design under hybrid uncertainty with considering COVID-19 pandemic disruption, Sustainable Production and Consumption, 30, 278–300.
[30] Kaur H., Singh S. P., Garza-Reyes J. A., Mishra N. (2019) Sustainable Stochastic Production and Procurement Problem for Resilient Supply Chain, Computers & Industrial Engineering, doi: https: //doi. org/10. 1016/j. cie. 2018. 12. 007
[31] Bairamzadeh S., Pishvaee M. S., Saidi-Mehrabad M. (2016) Multiobjective robust possibilistic programming approach to sustainable bioethanol supply chain design under multiple uncertainties, Ind. Eng. Chem. Res, 55 (1), 237-256.
[32] Fathollahi-Fard A. M., Ahmadi A., Mirzapour Al-e-Hashem S. M. J. (2020) Sustainable closed-loop supply chain network for an integrated water supply and wastewater collection system under uncertainty, Journal of Environmental Management 275, 111-277.
[33] Gholami-Zanjani S. M., Jabalameli M. S., Pishvaee M. S. (2021) A resilient-green model for multi-echelon meat supply chain planning. Computers and Industrial Engineering, 152, 107018.
[34] Kaur H., Singh S. P., Garza-Reyes J. A., & Mishra N. (2020) Sustainable stochastic production and procurement problem for resilient supply chain, Computers and Industrial Engineering, 139.
[35] Pavlov A., Ivanov D., Pavlov D., Slinko A. (2019) Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics, Annals of Operations Research.
[36] Kogler C., Rauch P. (2019) A discrete-event simulation model to test multimodal strategies for a greener and more resilient wood supply, Canadian Journal of Forest Research, 49(10), 1298–1310.
[37] Jabbarzadeh A., Fahimnia B., Rastegar S. (2019) Green and resilient design of electricity supply chain networks: A multiobjective robust optimization approach, IEEE Transactions on Engineering, 66(1).
[38] Dorneanu B., Masham E., Mechleri E., Arellano-Garcia H. (2019) Centralised versus localised supply chain management using a flow configuration model, In Computer Aided Chemical Engineering (Vol. 46) Elsevier Masson SAS.
[39] Jabbarzadeh A., Fahimnia B., Sabouhi F. (2018) Resilient and sustainable supply chain design: sustainability analysis under disruption risks, Int. J. Prod. Res. 56, (17), 5945–5968.
[40] Ivanov D. (2018) Revealing interfaces of supply chain resilience and sustainability: a simulation study, International Journal of Production Research, 56(10), 3507–3523.
[41] Mari S. I., Lee Y. H., Memon M. S. (2016) Sustainable and resilient garment supply chain network design with fuzzy multi-objectives under uncertainty, Sustainability (Switzerland), 8(10).
[42] Fahimnia B., Jabbarzadeh A. (2016) Marrying supply chain sustainability and resilience: A match made in heaven, Transportation Research Part E: Logistics and Transportation Review, 91, 306–324.
[43] Yılmaz Balaman S., Selim H. (2016) Sustainable design of renewable energy supply chains integrated with district heating systems: A fuzzy optimization approach, Journal of Cleaner Production,133, 863–885.
[44] Cardoso S. R., Paula Barbosa-P´ovoa A., Relvas S., Novais A. Q. (2015) Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty, Omega (United Kingdom), 56, 53–73.
[45] Tavana M., Kian H., Khalili Nasr A., Govindan K., Mina H. (2022) A comprehensive framework for sustainable closed-loop supply chain network design, Journal of Cleaner Production, 332, 129777.
[46] Ghaderi, A., Khanzadeh, C. (2019) A Combined Stochastic Programming and Robust Optimization Approach for Location-Routing Problem and Solving it via Variable Neighborhood Search algorithm. Journal of Operational Research and Its Applications, 16(4), 15-36.
[47] Mazidi M., Rezaei N., Ghaderi A. (2019) Simultaneous power and heat scheduling of microgrids considering operational uncertainties: A new stochastic p-robust optimization approach, Energy, 185, 239-253.
