Article ID Journal Published Year Pages File Type
11021074 Computers & Operations Research 2019 34 Pages PDF
Abstract
Recent technological advances, called Multicomponent Apheresis, allow tailoring the blood donations based on the demand and current inventory levels of blood products. Different from the most common type of blood donation (known as Whole Blood Donation), Multicomponent Apheresis allows the donation of one or more transfusable units of one or more blood products. Considering the changing demand for blood products during a planning horizon, deferral times, perishability of blood products, and limited donor pool, Multicomponent Apheresis provides an opportunity for increased donor utilization and hence a better managed blood supply chain. However, except some general guidelines proposed by blood donation organizations, the literature lacks analytical tools which can be used to fully explore the potential advantages of Multicomponent Apheresis, including the reduction in donation related costs and better utilization of the donor pool. In this paper, we develop models and solution approaches for tailoring the donations in order to quantify the potential benefits of Multicomponent Apheresis. More specifically, we define the Blood Donation Tailoring Problem where the objective is to minimize the total donation, inventory and disposal costs of blood products while satisfying the demand for blood products during a planning horizon by determining the donation schedule of a given donor pool. We develop a mathematical model and a column generation approach to tailor the donations. We also propose a more practical rule-of-thumb which can be easily implemented by the blood donation organizations. We compare the performances of the proposed approaches against a lower bound and the current practice at an apheresis facility. Finally, we also show that the proposed column generation approach can easily be modified to handle realistic aspects of the problem including stock-out and donor eligibility/preferences.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science (General)
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