Designing a robust blood supply chain model under conditions of uncertainty in demand

محورهای موضوعی : Supply chain management and logistics

Majid Motamedi ¹ , S.M Mousavi ² , Mohammad Hossein Darvish Motevali ³

1 - Department of Management, Nowshahr Branch Islamic Azad University, Nowshahr, Iran
2 - Department of Technical and Engineering, Faculty of Industrial Engineering, Islamic Azad University, Noshahr Branch, Mazandaran, Iran
3 - Department of Industrial Management, West Tehran Branch, Islamic Azad University, Tehran, Iran

تاریخ دریافت : 1403/06/01 تاریخ پذیرش : 1403/08/08 تاریخ انتشار : 1403/09/08

کلید واژه: Robust model, Blood supply chain, Demand, Uncertainty conditions, Waste, Deficiency,

چکیده مقاله :

The blood supply chain is one of the most important challenges in health and medical networks. In this paper, a non-linear multi-objective robust model of the blood supply chain under the condition of blood demand uncertainty is presented. The proposed model is a three-level model including supply, processing, and distribution of blood. The decision variables determined after solving the model include, the amount of blood collected from donors in the collection centers and sent to the blood centers, the product sent from the blood centers to the hospital, the optimal number of blood collection centers, the amount of product inventory in each center and hospital, and the amount of product shortage in each center and hospital. The aim of the proposed model is to reduce the costs of blood transfusion, shortages, and waste of blood and increase the reliability of the blood supply chain. To validate the proposed model, sensitivity analyses were performed using real data with different dimensions in the Barron solver in GAMS software. Sensitivity analyses of the model were carried out on the costs of waste, shortage, and the objective function. The results confirmed the validity and efficiency of the proposed model..

چکیده انگلیسی:

The blood supply chain is one of the most important challenges in health and medical networks. In this paper, a non-linear multi-objective robust model of the blood supply chain under the condition of blood demand uncertainty is presented. The proposed model is a three-level model including supply, processing, and distribution of blood. The decision variables determined after solving the model include, the amount of blood collected from donors in the collection centers and sent to the blood centers, the product sent from the blood centers to the hospital, the optimal number of blood collection centers, the amount of product inventory in each center and hospital, and the amount of product shortage in each center and hospital. The aim of the proposed model is to reduce the costs of blood transfusion, shortages, and waste of blood and increase the reliability of the blood supply chain. To validate the proposed model, sensitivity analyses were performed using real data with different dimensions in the Barron solver in GAMS software. Sensitivity analyses of the model were carried out on the costs of waste, shortage, and the objective function. The results confirmed the validity and efficiency of the proposed model..

منابع و مأخذ:

Aghiani, M., Jabbarzadeh, A., & Sajjadi, S. J., (2015). Presenting a robust optimization model for designing blood supply chain network in crisis situations with regard to reliability. Journal of Engineering and Quality Management, 5 (2), 85 -96.
Babazadeh Rafiei, A., Motamedi, M., Tahmoores, S., & Darvish Motevalli, M. H. (2023a). Design of a scenario-based multi-level and multi-objective mathematical model with the aim of reducing the risk of the blood supply chain in the conditions of the COVID-19 pandemic. Journal of Industrial Engineering and Management Studies, 10(2), 59-74.
Babazadeh Rafiei, A., Sohrabi, T., Motamedi, M., & Darvish Motevalli, M. H., (2023b). Identifying and ranking the risks of the blood supply chainin the conditions of the corona virus pandemic. The Scientific Journal of Iranian Blood Transfusion, 20 (2), 111-122.
Babazadeh Rafiei, A., Sohrabi, T., Motamedi, M., & Darvish Motevalli, M. H. (2024). A Robust Risk Management Model for the Blood Supply Chain during the COVID-19 Pandemic. Journal of Industrial Management Perspective, DOI: 10.48308/jimp.2024.234188.1520.
Bas, S., Carello, G., Lanzarone, E., & Yalçındağ, S. (2018). An appointment scheduling framework to balance the production of blood units from donation. European Journal of Operational Research, 265 (3), 1124-1143.
Cheraghi, S., & Hosseini-Motlagh, S. M., (2017). Optimal Blood Transportation in Disaster Relief Considering Facility Disruption and Route Reliability under Uncertainty. International Journal of Transportation Engineering, 4 (3), 225-254.
Cheraghi, S., Hosseini-Motlagh, S. M., & Ghatreh Samani, M., (2016). A Robust Optimization Model for Blood Supply Chain Network Design. International Journal of Industrial Engineering & Production Research, 27 (4), 425-444.
Clay, N. M., Abbasi, B., Eberhard, A., & Hearne. J., (2018). On the volatility of blood inventories, International Transactions in Operational Research, 25 (1), 215-242.
Davoodi Kiaklayeh, A., Paridar, M., & Tougeh, G. H. (2012). Calculating the unit cost of blood transfusion centers in Guilan province. Blood Research Quarterly, 9 (3), 346-352.
Derikvand, H., Hajimolana. S.M., Jabbarzadeh. A., & Najafi. S. E., (2020). A robust stochastic bi-objective model for blood inventory-distribution management in a blood supply chain. European Journal of Industrial Engineering, 14 (3), 369 – 403.
Ekici, A., Özener, O. O., & Çoban. E., (2018). Blood Supply Chain Management and Future Research Opportunities. Operations Research Applications in Health Care Management, International Series in Operations Research & Management Science, Chapter 10, 241-266.
Ensafian, H., Yaghoubi, S., & Modarres Yazdi, M., (2017). Raising quality and safety of platelet transfusion services in a patient based integrated supply chain under uncertainty. Computers and Chemical Engineering, 106, 355-372.
Fereiduni, M., & Shahanaghi, K., (2016). A robust optimization model for blood supply chain in emergency situations. International Journal of Industrial Engineering Computations, 7 (4), 535–554.
Ghatreh Samani, M. R., Torabi, S. A., & Hosseini-Motlagh, S. M., (2018). Integrated blood supply chain planning for disaster relief. International Journal of Disaster Risk Reduction, 27, 168-188.
Habibi-Kouchaksaraei, M., Paydar, M. M., & Asadi-Gangraj, E., (2018). Designing a bi-objective multi-echelon robust blood supply chain in a Disaster. Applied Mathematical Modelling, 55, 583-599.
Hamdan, B., & Diabat, A., (2020). Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation. Transportation Research Part E: Logistics and Transportation Review, 134, 101764.
Khalilpourazari, S., & Arshadi Khamseh, A., (2019). Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application. Annals of Operations Research, 283 (1), 355-393.
Jokar, A., & Hosseini-Motlagh, S. M., (2015). Impact of Capacity of Mobile Units on Blood Supply Chain Performance: Results from a Robust Analysis. International Journal of Hospital Research, 4(3), 101-105.
Motamedi, M., Movahedi, M. M., Rezaian Zaidi, J., & Rashidi Komijani, A., (2019). Designing a Non-Linear Mixed Integer Two-objective Math Model to Maximize the Reliability of Blood Supply Chain. Journal of Quality Engineering and Management, 8(4), 259-274.
Motamedi, M., Movahedi, M. M., Rezaian Zaidi, J., & Rashidi Komijan, A., (2020). Factors Affecting Blood Donation in the Blood Supply Chain Under Critical Conditions. Journal of Police Medicine, 9 (2), 71-78.
Mulvey, J. M., Vanderbei, R. J., Zenios, S. A. (1995), Robust optimization of large-scale systems. Operations research, 43 (2), 264-281.
Muriel, A. F. O., Brailsford, S., & Smith, H., (2014). A bi-objective optimization model for technology selection and donor’s assignment in the blood supply chain. Sistemas & Telemática, 12 (30), 9-24.
Nahofti Kohneh, J., Teymoury, E., & Pishvaee, M.S., (2016). Blood products supply chain design considering disaster circumstances (Case study: earthquake disaster in Tehran). Journal of Industrial and Systems Engineering, 9 (special issue on supply chain), 51 – 72.
Osorio, A. F., Brailsford, S. C., & Smith, H. K., (2018). Whole blood or apheresis donations? A multi-objective stochastic optimization approach. European Journal of Operational Research, 266 (1), 193-204.
Patil, P., Ray, P.K., & Saha, E. (2018). Modeling and Analysis of Distribution of Blood Stocks to Healthcare Units. Healthcare Systems Management: Methodologies and Applications, Managing the Asian Century, 115–131.
Pouraliakbari-Mamaghani, M., Ghodratnama, A., Pasandideh, S.H.R. & Saif, A., (2022). A robust possibilistic programming approach for blood supply chain network design in disaster relief considering congestion. Operational Research, 22 (3), 1987–2032.
Ramírez, A. P., & Labadie, N. (2017). Stochastic inventory control and distribution of blood products. Proceedings of the International Conference on Industrial Engineering and Operations Management Bogota, Colombia, 25-26.
Razavi, N., Gholizadeh, H., Nayeri, S., & Alizadeh Ashrafi, T., (2021). A robust optimization model of the field hospitals in the sustainable blood supply chain in crisis logistics. Journal of the Operational Research Society, 72(12), 2804-2828.
Rezaei-Malek, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Bozorgi-Amiri, A., (2016). An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Computers & Industrial Engineering, 94, 201-215.
Yu, C. S., Li, H. L., (2000). A robust optimization model for stochastic logistic problems. International Journal of Production Economics, 64 (1-3), 385-397.
Zandedel, M., Bozorgi Amiri, A., & Omrani, H., (2014). Presenting a model for locating blood donation sites with regard to disruption at the location. Journal of Industrial Engineering, 48, 33-43.