Abstract
This report demonstrates the power and usefulness of mathematical optimization as a de cision support tool in the medical services industry by presenting an application to dialysis service planning Models to predict the number of dialysis beds in a given region are usually population-based. Dialysis planners and providers have found a need to accommodate sparsely populated regions by making some allowance for patient travel times. A formal approach to incorporating travel times into dialysis planning, based on the formulation and solution of a mixed-integer programming model, is presented The development of a method for dialysis planning serves as a platform to demonstrate the use of integer programming to support decision making Major modeling principles are presented, output interpretation and sensitivity analysis are illustrated by examples; and computational requirements are dis cussed Key words. dialysis need forecasting, population-based model, travel time; math ematical optimization, mixed-integer programming; location, allocation
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