Determining optimal locations for blood distribution centers.

Abstract

Blood banks have to be thoughtful about supply chain decisions to effectively satisfy the blood product demand of hospitals. These decisions include the number and locations of distribution centers (DC), as this has a strong impact on both transportation cost and the ability to deliver emergency orders in time. We propose a mixed-integer linear programming approach to find optimal DC locations for supplying individual hospitals. The model maximizes the number of hospitals reachable from a DC within a given time-limit, and minimizes transportation cost. The minimal amount of data required is a set of hospital locations. The model can be further attuned to the user's needs by adding various model extensions. The model's use is demonstrated by two case studies, considering the blood banks of the Netherlands and Finland. For both case studies re-locating the DCs would result in a reduction of transportation cost of about 10% without affecting the reliability of delivery. In addition, to save facility exploitation costs, the number of DCs may be reduced in both countries while maintaining the reliability of delivery. The model was also shown to be robust against changes in hospital ordering behavior. We demonstrated the general usability and added value of the model by successfully optimizing the blood supply chains of the Netherlands and Finland, which differ substantially. Nonetheless, in both countries potential savings in both transportation and facility exploitation cost could be shown. The model code is open source and freely accessible online.