Volume 32, Issue 2 (IJIEPR 2021)                   IJIEPR 2021, 32(2): 0-0 | Back to browse issues page


XML Print


1- Department of Industrial Engineering, Payam-e-Noor University
2- , Department of Industrial Engineering, Payam-e-Noor University
3- Department of Industrial Engineering and Management, Shahrood University of Technology , sh.hosseini@shahroodut.ac.ir
Abstract:   (3721 Views)
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.
Full-Text [PDF 1625 kb]   (1167 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2020/07/26 | Accepted: 2021/06/19 | Published: 2021/06/19

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.