Showing 4 results for Blood Supply Chain
Seyyed-Mahdi Hosseini-Motlagh, Sara Cheraghi, Mohammadreza Ghatreh Samani,
Volume 27, Issue 4 (12-2016)
Abstract
The eternal need for humans' blood as a critical commodity makes the healthcare systems attempt to provide efficient blood supply chains (BSCs) by which the requirements are satisfied at the maximum level. To have an efficient supply of blood, an appropriate planning for blood supply chain is a challenge which requires more attention. In this paper, we address a mixed integer linear programming model for blood supply chain network design (BSCND) with the need for making both strategic and tactical decisions throughout a multiple planning periods. A robust programming approach is devised to deal with inherent randomness in parameters data of the model. To illustrate the usefulness of the model as well as its solution approach, it is tested into a set of numerical examples, and the sensitivity analyses are conducted. Finally, we employ two criteria: the mean and standard deviation of constraint violations under a number of random realizations to evaluate the performance of both the proposed robust and deterministic models. The results imply the domination of robust approach over the deterministic one.
Mostafa Soltani, R. Azizmohammadi, Seyed Mohammad Hassan Hosseini, Mahdi Mohammadi Zanjani,
Volume 32, Issue 2 (6-2021)
Abstract
The blood supply chain network is an especial case of the general supply chain network, which starts with the blood donating and ends with patients. Disasters such as earthquakes, floods, storms, and accidents usually event suddenly. Therefore, designing an efficient network for the blood supply chain network at emergencies is one of the most important challenging decisions for related managers. This paper aims to introduce a new blood supply chain network in disasters using the hub location approach. After introducing the last studies in blood supply chain and hub location separately, a new mixed-integer linear programming model based on hub location is presented for intercity transportation. Due to the complexity of this problem, two new methods are developed based on Particle Swarm Optimization and Differential Evolution algorithms to solve practical-sized problems. Real data related to a case study is used to test the developed mathematical model and to investigate the performance of the proposed algorithms. The result approves the accuracy of the new mathematical model and also the good performance of the proposed algorithms in solving the considered problem in real-sized dimensions. The proposed model is applicable considering new variables and operational constraints to more compatibility with reality. However, we considered the maximum possible demand for blood products in the proposed approach and so, lack of investigation of uncertainty conditions in key parameters is one of the most important limitations of this research.
Mehdi Seifbarghy, Mehri Nasrabadi,
Volume 34, Issue 3 (9-2023)
Abstract
One of the most key parts of a health system is the blood supply chain whose design is challenging due to the perishability of blood. In this research, an optimization model for multi-product blood supply chain network design is presented by considering blood deterioration. We consider a four-echelon blood supply chain that consists of blood donation centers, blood processing centers, blood products storage centers and hospitals as the user of the blood products. The locations of blood processing centers and blood products storage centers should be determined. Furthermore, considering different levels of technologies for blood processing, the suitable level for each opened center should be determined. In addition, different types of vehicle are also considered for blood transfer between different levels of the network. The objective is minimizing the total logistical costs including the costs of opening and running the blood processing centers and blood product storage centers and blood products transfer costs between different levels of the supply chain. Finally, we apply the given model to a real case study in Iranian blood supply chain, and sensitivity analysis is performed on some parameters. In the end, some managerial insights are given
Mohammad Reza Ghatreh Samani, Jafar Gheidar-Kheljani,
Volume 34, Issue 3 (9-2023)
Abstract
In this paper, a brief review of the recently developed blood supply chain (BSC) management studies is firstly presented. Then, a first-ever multi-objective robust BSC model is proposed, which is inspired by the need for an integrated approach towards improving the performance of BSC networks under uncertain conditions. The network efficiency by minimizing cost, adequacy by providing reliable and sufficient blood supply, and effectiveness by controlling blood freshness are aimed at the proposed model. A two-phase approach based on robust programming and an augmented epsilon-constraint method is devised to model the uncertainty in parameters and provides a single-objective counterpart of the original multi-objective robust model. We investigate a case to illustrate the real-world applicability of the problem. The research comes to an end by performing some sensitivity analyses on critical parameters, and the results imply the capability of the model and its solution technique.
