1 Operations Research, Department of Informatics and Mathematical Modeling, Technical University of Denmark2 Department of Informatics and Mathematical Modeling, Technical University of Denmark3 unknown4 Department of Management Engineering, Technical University of Denmark
Typically, ground staff scheduling is centrally planned for each terminal in an airport. The advantage of this is that the staff is efficiently utilized, but a disadvantage is that staff spends considerable time walking between stands. In this paper a decentralized approach for ground staff scheduling is investigated. The airport terminal is divided into zones, where each zone consists of a set of stands geographically next to each other. Staff is assigned to work in only one zone and the staff scheduling is planned decentralized for each zone. The advantage of this approach is that the staff work in a smaller area of the terminal and thus spends less time walking between stands. When planning decentralized the allocation of stands to flights influences the staff scheduling since the workload in a zone depends on which flights are allocated to stands in the zone. Hence solving the problem depends on the actual stand allocation but also on the number of zones and the layout of these. A mathematical model of the problem is proposed, which integrates the stand allocation and the staff scheduling. A heuristic solution method is developed and applied on a real case from British Airways, London Heathrow Airport. This study shows that decentralization generally increases the number of staff needed compared to centralized planning. The case study also shows that there is a trade-off between the extra staff needed and the quality of the stand allocation. Furthermore, the robustness of solutions with respect to disruptions deteriorates with the number of zones. In practice, the "cost" of introducing decentralization should therefore be weighted against the benefits gained.
Zoning; Decentralization; Simulated Annealing; Ground Staff Scheduling; Stand allocation