A Robust Stochastic Programming Approach for Blood Collection and Distribution Network Design (original) (raw)
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Computers & Operations Research, 2015
Major challenges in the management of the blood supply chain are related to the shortage and wastage of the blood products. Given the perishable characteristics of this product, storing an excessive number of blood units on inventory could result on the wastage of this limited resource. On the other hand, having shortages may result in cancellations of critical health related activities and as a result a potential increase on fatality rates at hospitals. This paper presents integer programming models to minimize the total cost, shortage and wastage levels of blood products at a hospital within a planning horizon. The primary focus is on the red blood cells and the platelet components of the whole blood cells. The stochastic and deterministic models included consider uncertain demand rates, demand for two types of patients, and crossmatch-to-transfusion ratio. Results show wastage rates decreasing from 19.9% to 2.57% on average. In addition, the shortages and total cost are reduced 91.43% and 20.7% respectively for a given capacity increases. Computational results are included and discussed.
Stochastic inventory control and distribution of blood products
2017
Inventory control in perishable products supply chain is one of the biggest challenges today, especially for medicines and blood products supply chain. Shortage can increase the mortality risk at hospitals, on the contrary, high levels of inventory could generate wastage of these resources. This paper studies the problem of inventory control and distribution of blood products. This study determines the number of blood units to be processed by the blood center and the number of units of blood products to be ordered by hospitals to minimize the total cost and the shortage and wastage levels in blood supply chain. Two optimization models are formulated: A Mixed Integer Linear Programming (MILP) Model for known demands and a Stochastic Programming (SP) Model for the case where demands are uncertain, considering multiple periods, types of blood and life time of products. Datasets are generated to evaluate the efficiency of proposed models for a multi-hospitals single-blood center system....
Mathematical modeling for optimizing the blood supply chain network
Modern Supply Chain Research and Applications
PurposeThis research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.Design/methodology/approachSince the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of th...
Journal of Healthcare Engineering, 2020
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. 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. Results. Based on the results,...