Mathematical modelling to support blood collection for the Welsh Blood Service

Williams, Emily Paige 2022. Mathematical modelling to support blood collection for the Welsh Blood Service. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

Human blood is a scarce resource and its role in healthcare is fundamental, with donated blood saving the lives of many on a daily basis. The blood supply chain is responsible for the transfer of blood from donor to the recipient, but the availability of such an invaluable resource as human blood is ultimately attributable to the many voluntary donors. Thus, the efficiency of the collection of donated blood is crucial to the downstream effectiveness of the blood supply chain. Working in partnership with the Welsh Blood Service, our aim is to create a decision support tool to aid the scheduling process to match supply and demand of blood products, whilst minimising costs and wastage in the system. We present an integer linear programme model that consists of two stages. The first stage schedules mobile blood donation clinics, considering over 300 locations, with the objective to minimise both the number of clinics scheduled within the planning horizon and the amount of blood collected that exceeds the demand. The second stage assigns workers to each scheduled clinic, with the objective of minimising costs such as overtime costs. Both stages of this scheduling model are developed in Python and are solved using PuLP - an open source Python package which utilises COIN-OR CBC solver. Test instances are designed and the experimental results are presented which demonstrate the effectiveness of the two-stage model to improve cost and time efficiencies of the collections process at the Welsh Blood Service, in addition to enabling the matching of supply to demand. Finally, some insights regarding the staffing levels of each region are discussed

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Mathematics
Date of First Compliant Deposit:	27 May 2022
Last Modified:	10 Jun 2023 02:02
URI:	https://orca.cardiff.ac.uk/id/eprint/150083

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