Integrated shift and break scheduling for airline ground staff under flight delay uncertainty

Efficient ground personnel scheduling is critical for reliable airline operations. This paper presents an integrated two-stage stochastic optimization framework for shift and break scheduling of airline ground staff, incorporating employee exchangeability and service-level constraints under delay uncertainty. Two model variants are developed: a baseline shift and break scheduling model with predetermined break times and an ex-post variant with scenario-dependent breaks. The models explicitly consider understaffing and overstaffing costs, and allow for limited cross-pool and cross-skill employee exchangeability. To address risk-sensitive planning requirements, the baseline model is extended with service-level constraints that ensure understaffing remains bounded in all but a specified number of extreme scenarios. The models are evaluated on six synthetic demand profiles representing different flight schedule patterns and on a case study inspired by a major European airline. The computational experiments examine the effects of demand shape, understaffing cost, delay variance, correlation, and workforce exchangeability. The results show that stochastic planning substantially outperforms deterministic planning, achieving cost reductions of up to 34%. The value of perfect information remains limited in most settings, indicating that the stochastic framework already captures most of the benefit of improved foresight. Ex-post break scheduling yields only modest additional gains, whereas employee exchangeability emerges as a major source of flexibility and cost efficiency, particularly under correlated disruptions. The service-level formulation provides a practical alternative when explicit reliability guarantees are preferred over penalty based modeling. This research highlights the importance of integrating uncertainty, operational flexibility, and performance in tactical workforce scheduling for complex airline operations.