Airport Logistics : Modeling and Optimizing the Turn-Around Process
Abstract: The focus of this licentiate thesis is air transportation and especially the logistics at an airport. The concept of airport logistics is investigated based on the following definition: Airport logistics is the planning and control of all resources and information that create a value for the customers utilizing the airport. As a part of the investigation, indicators for airport performance are considered.One of the most complex airport processes is the turn-around process. The turn-around is the collective name for all those activities that affect an aircraft while it is on the ground. In the turn-around process almost all of the actors operating at the airport are involved and the process is connected to other activities which take place on airside, in the terminal as well as in the control tower. This makes the turn-around process an excellent focal point for studying airport logistics.A detailed conceptual model of the turn-around process is developed and a simplified version of this is implemented in a computerized simulation program. The aim of the simulation is to enable the assessment of various logistical operations involved in turn-around, and their impact on airport performance. The flow of support vehicles serving the aircraft with fuel, food, water etc during the turn-around is received particular attention. The output from the model can be used as indicators for the airport performance.One of the most interesting support flows to study is the flow of de-icing trucks. De-icing is performed to remove ice and snow from the aircraft body and to prevent the build up of new ice. There is a limited time span prior the take off, within which de-icing has to be performed. This makes the time of service critical. An optimization approach is developed to plan a schedule for the de-icing trucks. Scheduling the flow of de-icing trucks can be seen as a heterogeneous vehicle routing problem with time windows. The objective of the optimization is total airport performance and a heuristic method is used to solve the problem.The optimized schedule for the de-icing trucks is used as input in the simulation model. The schedule optimized for the entire airport is compared to a schedule based on a simpler scheduling rule as well as a schedule optimized for the de-icing company. By running the model with the different routings, it is found that the schedule optimized for the entire airport gives the best results according to the indicators specified for measuring airport performance.
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