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Stochastic Inventory Model for Minimizing Blood Shortage and Outdating in a Blood Supply Chain under Supply and Demand Uncertainty.
- Source :
-
Journal of healthcare engineering [J Healthc Eng] 2020 Aug 29; Vol. 2020, pp. 8881751. Date of Electronic Publication: 2020 Aug 29 (Print Publication: 2020). - Publication Year :
- 2020
-
Abstract
- Purpose: Blood, like fresh produce, is a perishable element, with platelets having a limited lifetime of five days and red blood cells lasting 42 days. To manage the blood supply chain more effectively under demand and supply uncertainty, it is of considerable importance to developing a practical blood supply chain model. This paper proposed an essential blood supply chain model under demand and supply uncertainty.<br />Methods: This study focused on how to manage the blood supply chain under demand and supply uncertainty effectively. A stochastic mixed-integer linear programming (MILP) model for the blood supply chain is proposed. Furthermore, this study conducted a sensitivity analysis to examine the impacts of the coefficient of demand and supply variation and the cost parameters on the average total cost and the performance measures (units of shortage, outdated units, inventory holding units, and purchased units) for both the blood center and hospitals.<br />Results: Based on the results, the hospitals and the blood center can choose the optimal ordering policy that works best for them. From the results, we observed that when the coefficient of demand and supply variation is increased, the expected supply chain cost increased with more outdating units, shortages units, and holding units due to the impacts of supply and demand fluctuation. Variation in the inventory holding and expiration costs has an insignificant effect on the total cost.<br />Conclusions: The model developed in this paper can assist managers and pathologists at the blood donation centers and hospitals to determine the most efficient inventory policy with a minimum cost based on the uncertainty of blood supply and demand. The model also performs as a decision support system to help health care professionals manage and control blood inventory more effectively under blood supply and demand uncertainty, thus reducing shortage of blood and expired wastage of blood.<br />Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper.<br /> (Copyright © 2020 Han Shih and Suchithra Rajendran.)
- Subjects :
- Algorithms
Blood Banks economics
Blood Preservation
Equipment and Supplies
Erythrocytes cytology
Health Care Costs
Hospitals
Humans
Linear Models
Models, Theoretical
Sensitivity and Specificity
Software
Blood Banks supply & distribution
Blood Transfusion statistics & numerical data
Models, Organizational
Uncertainty
Subjects
Details
- Language :
- English
- ISSN :
- 2040-2309
- Volume :
- 2020
- Database :
- MEDLINE
- Journal :
- Journal of healthcare engineering
- Publication Type :
- Academic Journal
- Accession number :
- 32952991
- Full Text :
- https://doi.org/10.1155/2020/8881751