Residents in this setting found CNMP management to be difficult. They lacked confidence in managing CNMP and did not gain confidence over the course of training. Substantial opportunities exist for improving resident education in CNMP.
Research on learning effects in mathematical programming models for optimum resource allocation has called attention to the difficulty in solving such models in their original nonlinear form. In this paper, systematically varying sizes of linear segments are designed to approximate productivity changes along the learning curve, and a single separable linear programming model is developed. With production complementarity and learning transmission between products, a more realistic resource allocation and production scheduling problem emerges. Two cases of learning transmissions are considered, and the model design process, which defines a decision problem that can be solved by a simplex algorithm, is demonstrated.Subjat Arwr: L a m i n g Models, Mathanahd Rvgmmdng, and Rcsoww Allocarom
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