Absenteeism Prediction & Labor Force Optimization in Rail Dispatcher Scheduling

Scheduling dispatchers in the Rail industry is difficult because of training requirements, unplanned employee absences, and the nature of shift work. This project uses past data on absences to build a model to predict unplanned absences. It also uses Monte Carlo simulation to evaluate the tradeoffs among extra staff, the training levels of employees, and required overtime.

Authors: Taylor Jensen and Qi Sun
Advisor: Dr. Tony Craig