Optimal staffing of specialized programme trainees under uncertainty
Özdemir Akyıldırım, Öznur
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We propose a stochastic model and provide an easy-to-implement optimization tool for admission decisions to specialized training programmes designed for service industries. The model can be applied for staffing of trainees in medical residency programmes, vocational schools, management trainee programmes, and similar. Especially towards graduation, trainees in these programmes substantially contribute to workforce of their affiliated institutions, thus having a targeted number of advanced level students become a potential performance metric for administration. For uncertain attrition rates and study duration, we model and provide an iterative solution algorithm to find the optimal annual admission number for these programmes. Our numeric analysis results show that the solution is robust to changes in attrition and study duration probabilities; hence, our model is robust against specification errors for these parameters, which could be hard to estimate due to data unavailability and fluctuations in educational and economic conditions.