This paper addresses the manufacturing and distribution of short-lived radio-pharmaceuticals which are mainly used in diagnostic imaging studies. We develop a mixed integer nonlinear optimization model that is flexible enough to capture the complex underlying nuclear physics of the production process of fludeoxyglucose (FDG), which is widely used in oncology and cardiology, as well as the time sensitive constraints of the distribution of the final products to geographically dispersed medical imaging centers. The model synergistically integrates the production and delivery requirements in a multi-period framework. It generates the optimal amount of radioactivity needed to satisfy the demand placed by imaging centers during a full day and provides the minimum cost transportation routes that guarantee the on-time delivery of the doses. We present numerical results that demonstrate the usefulness of the model by substantial cost savings in both the manufacturing and transportation phases.
Citation
In Proceedings of: 10th International Conference on Modeling Optimization and Simulation (MOSIM), Montreal, Canada, August 22-24, 2016.