  We propose a simulation-optimization-based methodology to improve the way
that organ transplant offers are made to potential recipients. Our policy can
be applied to all types of organs, is implemented starting at the local level,
is flexible with respect to simultaneous offers of an organ to multiple
patients, and takes into account the quality of the organs under consideration.
We describe in detail our simulation-optimization procedure and how it uses
underlying real-world transplant data to inform the decision-making process. We
present results using our liver and kidney models, where we show that, under
our policy recommendations, more organs are utilized and the required times to
allocate the organs are reduced -- sometimes dramatically.
