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Decision-making processes often contain more than one objective. In technology selection in the blood collection processes, the cost related to the collection technology and the amount of donors required to meet the demand are in conflict. In the same way, in the blood supply chains decisions become more complex when features of the system such as blood type proportions and compatibilities are considered. In order to generate solutions to this problem, an Integer Linear Programming is proposed considering total cost minimisation and amount of donors required. This model also considers distinct constraints such as capacity, proportionality, and demand fulfilment among others. Open Solver 2.1 was used to solve this problem in combination with Visual Basic for Applications for generating the set of efficient solutions that make up the Pareto front through the augmented Epsilon constraint algorithm.
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