A Model for Supply-Chain Decisions for Resource Sharing with an Application to Ventilator Allocation to Combat COVID-19

Sanjay Mehrotra; Hamed Rahimian; Masoud Barah; Fengqiao Luo; Karolina Schantz

Case I and II are generated to develop average demand scenario representations that use the information provided in the CI given in [25] in two different ways. In Case I, it is assumed that the mean is the median of the demand distribution (i.e., the right-and left-tail of the demand distribution have 0.5 probability). We randomly generated a number to indicate which tail to sample from, where both tails have the same 0.5 probability of being chosen. Once the tail is determined, we divided the tail into 50 equally-distanced partitions, and chose a random partition to uniformly sample from. We repeated this process for all days and states. We sampled from the same tail and partition for all days and states, although the range from which we sample depends on the CI. In this case, all scenarios are equally likely.