Efficient baggage handling is essential for airport operations. Delays due to congestion or baggage mishandling can severely impact operational efficiency and passenger satisfaction. As rising passenger traffic increasingly burdens existing infrastructures, optimizing the performance of baggage handling systems represents a critical challenge. This paper addresses the integrated management of airport baggage handling operations by considering the daily coordinated allocation of check-in desks and baggage sorting piers for outbound flights. We develop a comprehensive mixed-integer programming (MIP) formulation that incorporates essential constraints to reflect complex real-world operational conditions. The model aims to minimize mean bag travel time within the baggage handling system, thereby increasing system capacity without requiring expensive infrastructure expansions or technological upgrades, while mitigating the incidence of mishandled bags. Tested on real-world instances from Terminal 1 of Paris-Charles de Gaulle Airport, the proposed model produces promising results. It successfully prevents mishandled bags and achieves a 20% improvement in mean bag travel time compared to historical allocation decisions. This gain is achieved by eliminating transfers between sorters, prioritizing high-speed equipment, and reducing congestion in the sorting gallery. Robustness analyses confirm the model's stability under challenging conditions and its ability to balance mathematical optimality with rigorous operational requirements. From a managerial perspective, the results demonstrate that Terminal 1 of Paris-Charles de Gaulle Airport could handle both a 30% increase in flight volume and degraded sorting system speeds with its existing infrastructure by adapting internal policies through the proposed optimization framework.

Keywords

Resource Allocation, Process Optimization, Mixed-Integer Linear Programming, Airport Operations, Baggage Handling.