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Description: A commercial aircraft cannot freely use the available airspace but instead has to stick to a three-dimensional network of segments similar to a car in a road network. In this network it faces several variable and interdependent costs in the form of travel time, fuel consumption and overflight charges. These are also highly dependent on other factors such as weather conditions, aircraft performance, take-off time and weight as well as the changing availability of elements in the graph. This is further complicated by the distinction of separate flight phases that challenge the standard notion of a graph with predetermined nodes and arcs. Therefore when trying to find either a distance, fuel, time or cost minimal trajectory for a specific aircraft between an origin and a destination airport, one faces a very complex shortest path problem in the airway network graph that even for strong implifications is often NP-hard. This thesis will focus on exploring the costs that occur in this graph and that are associated with the aircraft performance. Here we will rely on actual performance and weather data supplied by Lufthansa Systems AG in Frankfurt and analyze whether they meet the requirements necessary for common algorithms such as the First-in, First-out property. Since it is vital for any shortest path algorithm to have a fast and accurate way of determining the costs in the graph, we will face two problems regarding the calculation of aircraft performance during cruise as well as the calculation of the so-called air distance. So far these problems have been approached by the industry with rudimentary approximative methods. We will reformulate them as initial value problems and try to find good approximations using both general Runge-Kutta methods as well as a novel approach which relies on finding piecewise linear approximations of some primitive integrals in pre-processing. Computations will show that these approaches deliver fast and accurate results.