A high-level computing algorithm for diverging and converging branch nonserial dynamic programming systems

AbstractWe present high-level computing algorithms for efficiently processing the diverging and converging branch systems in nonserial dynamic programming. A special technique in devised for processing the network functions such that the minimum amount of storage is employed. It is shown that if k is the discretization level of the state and decision variables then the space complexities are O(k) and O(k2) for the diverging and converging branch systems, respectively. The resultant time complexities are also developed. These savings in computational complexities enhance the attractiveness of dynamic programming as a tool for processing more complex nonserial systems

Physician Supply and Surgical Demand Forecasting: A Regional Manpower Study

This paper discusses the methods and the results of a forecast for the demand for operative and obstetrical procedures and the supply of anesthesiologists in Cuyahoga County, Ohio. The techniques and results of a ten-year forecast for the demand for and supply of anesthesiologists and auxiliary personnel in greater Cleveland are discussed. Several regression models were used to forecast supply based on population, number of physicians, and the income per capita. The demand models were based on population, age and sex distribution projections, and historical data regarding operative and obstetrical procedures. The results of these "objective" models were then compared to forecasts under uncertainty generated by a panel of experts using the Delphi Method. Alternative states of health care delivery were investigated and implications for future anesthesiologist manpower requirements detailed.