Airline crew ground transportation presents a unique optimization challenge, balancing efficiency, cost, and strict operational constraints. Factors such as fluctuating daily schedules, regulatory time limits, and labor agreements create a complex environment where traditional planning methods often lead to low vehicle occupancy and increased operational costs.
This presentation explores an innovative approach to improving crew transport efficiency through advanced clustering and routing techniques. By leveraging geo-temporal data and strategic grouping methodologies, we establish a framework that enhances ride-sharing opportunities while maintaining compliance with duty-time and other Union regulations. Additionally, a structured planning mechanism integrates these optimized clusters into a dynamic routing model, ensuring adaptability to real-world scheduling variability.
A key aspect of this approach is the integration of operational constraints into the optimization process. By incorporating geographic clustering with time-window constraints and penalty-based heuristics, we enable flexible yet efficient transport planning. The model balances efficiency with practical constraints. This scalable framework is designed to improve transport efficiency, reduce costs, and support sustainable crew logistics in dynamic airline environments.
Attendees will gain insights into the underlying principles of this approach, its practical applications, and how it can be adapted to different operational contexts. The presentation will highlight key challenges, innovative methodologies, and the potential impact on airline resource optimization.