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When an airline experiences disruptions during irregular operations (IROPs)—such as weather delays and cancellations—crew schedules can quickly fall apart. While existing recovery tools can fix/recover broken sequences, they often leave some flight legs un-sequenced and un-crewed due to feasibility of schedules and contract requirements. Re-sequencing these orphaned legs becomes a manual, time-sensitive, and costly task. Sequence Builder is a proof-of-concept tool designed to optimize/automate this process. It leverages a network graph structure and a multi-label shortest path algorithm to generate feasible and contractually legal crew sequences from un-sequenced legs. These candidate sequences are then evaluated using a Mixed Integer Program (MIP), optimizing for cost efficiency, sequence attractiveness, and effective crew utilization. The final sequences are fed into existing proffering systems, allowing award to lineholders or reserves—and ultimately improving operational resilience during IROPs.

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Biomathematical models estimate aircrew fatigue based on sleep-wake patterns, but fatigue scores alone may not fully capture operational risks. Fatigue-related incidents often result from complex duty characteristics that extend beyond cumulative sleep loss. Alternative approaches that integrate probabilistic associations between duty patterns and reportable incidents can allow for the identification of duties that may not appear highly fatiguing yet carry an elevated incident risk, or vice versa. By incorporating a broader risk perspective, this approach enhances fatigue management strategies and supports more effective operational decision-making, improving both safety and performance in safety-critical industries.

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Panelists: Raquel McQueen (Viva Aerobus), Dondon Anglo (Cebuu Pacific), Tristan Thiebaut (Bearing Point), Fanny Nip (Cathay Pacific), Toulou Esfandeh (American Airlines), Alex Gareau (Porter Airlines)

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Traditionally, bio-mathematical fatigue models have been used primarily to mitigate crew fatigue risks by restricting risk exposure while optimizing crew pairings and rosters—serving as a complement to regulatory flight and duty time limits. However, these models can also play a critical role in safeguarding operational flexibility. This presentation explores their expanded use in ensuring that fatigue-related rules do not unnecessarily constrain viable scheduling solutions where no elevated risk exists. We will present quantifiable comparisons between different approaches, unpack the underlying mechanisms, and discuss key considerations for adopting this perspective for both strategic and tactical crew planning.

The Flight Operations team at United Airlines has many strategies to re-crew and resolve pilot pairings that remain 'open', without a crew. One of the ways crew schedulers resolve open pairings is to split the pairing into multiple, legal, sub-pairings and assign reserve pilots to each portion. We present a recently deployed mixed-integer linear programming decision support model that aids crew schedulers in determining (i) which open pairings are the best candidates to split, and (ii) the most effective way to split them. The multi-objective model balances added crew cost and network-wide reserve availability to consider the future impact of pairing split decisions, and provide the best solution according to current crew scheduler priorities.

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