Corporate Blog

Using deep learning models to reduce crew standby costs in airline operations

Using deep learning models to reduce crew standby costs in airline operations
Airlines factor standby crew in their planning as a buffer in case unexpected events cause deviations to operational plans, such as disruptions or last-minute crew roster changes. In these situations, standby buffering is a critical part of crew planning to safeguard the passenger experience and brand reputation. Additionally, the cost of reassigning crews to flights is significantly higher without standby buffers. Balancing crew standbys with actual utilization on the day of operations is challenging. Our analysis indicates that, on average, only 30%-40% of crew standbys are used, representin...
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