We introduce an effort to create prototype capabilities to enable the Analysis of Mobility Platform (AMP) to produce airlift schedules for the Agile Transportation for the 21 st  Century (AT21) program at the United States Transportation Command (USTRANSCOM) that are more robust and flexible to real world changes. AMP currently uses a deterministic simulation-based process to produce schedules, effectively assuming that execution occurs under expected conditions. We have designed robustness and flexibility heuristics that generate different candidate schedules, and a stochastic simulation that varies departure delays using a probabilistic model based on real-world Global Decision Support System (GDSS) data. Through stochastic simulated executions of candidate schedules and several robustness/flexibility measures, including a  schedule content comparison  metric, our approach seeks the candidate schedule that best balances solution quality with robustness/flexibility. We present our heuristics, stochastic model and measures, and summarize our initial findings and next steps for robust and flexible AT21 scheduling.
['Talib S. Hussain', 'Richard Shapiro', 'Steve Sommer', 'Nicole Ogden', 'John O’Dea', 'John Collins', 'Julia Baum', 'Adan E. Vela', 'Allison Chang']
Robust and flexible air mobility scheduling using stochastic simulation-based assessment