A robust mathematical model for platelet supply chain considering social announcements and blood extraction technologies

Since the only source of supplying platelets is available donors, evaluating donors' treatments plays a vital role in the supply chain. According to the investigation of a real study, four main issues have directly affect the quantity of platelet donation in the supply chain, namely, (1) different types of donors as first-time secondary polycythemia donors, experienced secondary polycythemia donors and regular donors, (2) number of booked and non-booked donors within and after working hours, (3) submitting social announcements such as banner ads, social media, and newspapers, and (4) allocating blood extraction technologies to hospitals. Moreover, dealing with demand fluctuation and short lifespan of platelets is also a critical point. Noteworthy, since the technology allocation in hospitals is expensive, the hospitals' efficiency is determined by a fuzzy analytic hierarchy process approach. Therefore, to address these issues, firstly, we create a balance between hospitals' efficiency as suppliers and costs in a bi-objective mixed-integer programming model. Then, a robust-stochastic approach is considered to tackle the uncertainty in input data. The results validate in a real case study to facilitate practitioners making proper decisions.