Abstract: A method for predicting survival rates of a prospective organ recipient is disclosed. The method may include receiving a first dataset that includes characteristics of previous persons in need of a transplant that received or did not receive the organ transplant and their respective actual survival rates. The method may further include receiving a second dataset that includes characteristics of a prospective organ recipient and characteristics of a donor organ available for an organ transplant into the prospective organ recipient. The method may then calculate the estimated survival rates over a predetermined of the prospective organ recipient based on whether the prospective organ recipient has the organ transplanted. Next, a graph may be generated showing the estimated survival rates of the prospective organ recipient based on whether the prospective organ recipient receives and does not receive the organ transplant, which may be displayed a graphical user interface.

Abstract: Prediction methods that anticipate the outcome of a detailed optimization step are used in lieu of or in conjunction with actual optimization to improve response time and reduce required computational resources for optimization problems having a hierarchical structure. Decomposition of the optimization problem into sub-problems and sub-sub-problems is, itself, an optimization process which is iteratively performed while preferably guided by prediction of the quality of solutions to the problems into which the “master” optimization problem may be decomposed. Prediction also reduces the requirements for computational resources and allows more decompositions to be examined within the available time in order to arrive at a more nearly optimal decomposition as well as a more nearly optimal solution. Prediction is selectively used when it is determined that such a benefit is probable.

Abstract: Prediction methods that anticipate the outcome of a detailed optimization step are used in lieu of or in conjunction with actual optimization to improve response time and reduce required computational resources for optimization problems having a hierarchical structure. Decomposition of the optimization problem into sub-problems and sub-sub-problems is, itself, an optimization process which is iteratively performed while preferably guided by prediction of the quality of solutions to the problems into which the “master” optimization problem may be decomposed. Prediction also reduces the requirements for computational resources and allows more decompositions to be examined within the available time in order to arrive at a more nearly optimal decomposition as well as a more nearly optimal solution. Prediction is selectively used when it is determined that such a benefit is probable.