Industrial Innovations

Industrial Innovations

Presenting a Bi- objective Integrated Model of Blood Supply Chain Network Design with the Approach of Increasing the Quality of Products

Document Type : Original Article

Author
Fateme Rashidian
Ph.D student, industrial engineering, Faculty of Engineering, University of Kurdistan, Kurdistan, Iran.
https://doi.org/10.61186/jii.1.3.255
Abstract
The blood supply chain plays an essential role in the health supply chain network, especially when a disaster occurs, the need for a sufficient blood supply chain to improve the condition of patients increases greatly. Therefore, paying attention to the existing requirements in the network design plays an important role in improving the service sector as much as possible. Blood transfusion is a complex process that carries the risk of reduced quality at every step, from donors to patients. Therefore, maintaining a high quality of blood products is crucial in the supply chain. Additionally, the transportation of blood products is costly due to specialized equipment. This paper presents a bi-objective model for designing a blood supply chain network. The first objective is to minimize costs, while the second objective is to maximize the quality of the blood products. A preliminary model is introduced, taking into account critical parameters. The proposed method is tested and validated through a case study of a blood network. The results show that the cost objective function is 42 units for small problems and 664 units for medium problems, while the objective function for blood quality is also considered in the same solutions. The LP- metric algorithm provides acceptable Pareto solutions, with efficiency of 1678 units for small problems and 24392 units for medium problems. In the case of small problems, all donors go to the main center, while for medium problems, temporary centers are established in addition to the main centers during certain time periods.
Keywords
Supply chain network design
Quality of products
LP- metric algorithm
[1] Nagurney A, Masoumi AH, Yu M. Supply chain network operations management of a blood banking system with cost and risk minimization. Computational management science. 2012;9:205-31. 
[2] Mvere D, Bond K. The blood cold chain: guide to the selection and procurement of equipment and accessories: World Health Organization, 2002. 
[3] Rudmann SV. Textbook of blood banking and transfusion medicine: Elsevier Health Sciences, 2005. 
[4] Taymory Naghadeh H, Fallahtafti M, Shoshtarian SMM. Evaluation of in vitro quality of none agitated platelet concentrate. Medical Sciences Journal of Islamic Azad University. 2013;23:107-12. 
[5] Sha Y, Huang J. The multi-period location-allocation problem of engineering emergency blood supply systems. Systems Engineering Procedia. 2012;5:21-8. 
[6] Zahiri B, Mousazadeh M, Bozorgi-Amiri A. A robust stochastic programming approach for blood collection and distribution network design. International journal of research in industrial engineering. 2014;3:1-11. 
[7] Zahiri B, Torabi S, Mousazadeh M, Mansouri S. Blood collection management: Methodology and application. Applied Mathematical Modelling. 2015;39:7680-96. 
[8] Zahiri B, Pishvaee MS. Blood supply chain network design considering blood group compatibility under uncertainty. International journal of production research. 2017;55:2013-33. 
[9] Samani MRG, Hosseini-Motlagh S-M. An enhanced procedure for managing blood supply chain under disruptions and uncertainties. Annals of Operations Research. 2019;283:1413-62. 
[10] Rahmani D. Designing a robust and dynamic network for the emergency blood supply chain with the risk of disruptions. Annals of Operations Research. 2019;283:613-41. 
[11] Samani MRG, Hosseini-Motlagh S-M, Sheshkol MI, Shetab-Boushehri S-N. A bi-objective integrated model for the uncertain blood network design with raising products quality. European journal of industrial engineering. 2019;13:553-88. 
[12] Haghjoo N, Tavakkoli-Moghaddam R, Shahmoradi-Moghadam H, Rahimi Y. Reliable blood supply chain network design with facility disruption: A real-world application. Engineering Applications of Artificial Intelligence. 2020;90:103493. 
[13] Eslamipoor R, Nobari A. A reliable and sustainable design of supply chain in healthcare under uncertainty regarding environmental impacts. Journal of applied research on industrial engineering. 2023;10:256-72. 
 
Industrial Innovations
Volume 1, Issue 3 - Serial Number 3
Summer 2023
Pages 255-270

  • Receive Date 01 November 2023
  • Revise Date 04 December 2023
  • Accept Date 12 December 2023