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Aviation has grown dramatically over the last decades. Worldwide air traffic is expected to continue to grow at rates of 3-5% per year. Air traffic currently experiences long delays at major airports, noticeable impact on the environment, and high work load on air traffic controllers. Future operational concepts to deal with these problems and to support sustainable growth of the Air Navigation Industry have been defined by International Civil Aviation Organization (ICAO) and major Air Traffic Control (ATC) authorities including both Eurocontrol and Federal Aviation Administration (FAA). One of these concepts is User Preferred Routes (UPR), representing the routes with the best business outcome from the airspace user s perspective. Aircraft would generally be free to fly user-preferred routes, and modify their trajectories without, or with minimal, intervention by ATC. There has been limited research on optimisation methods for UPR and on investigating the impact of UPR on the environment, delays, safety, etc. In this thesis a framework is designed and developed to find user preferred routes for flights and evaluate the UPR concept. The main contribution of the thesis is a set of three different methods for finding UPR. Through the experiments with the two first methods, which are based on Genetic Algorithms and Learning Classifier Systems and act as the black and white box optimisation approaches, we found the pros and cons for these different optimisation philosophies. The third method is a scalable algorithm that is fast and reliable. It can optimise routes efficiently for different mixes of users. To enable the investigation and optimisation of UPR, a simulation and evaluation environment is established. In this environment, I developed a real time weather system to retrieve and process weather data. This data is then stored in a database for aviation decision support in general and for aircraft UPR in particular. Second, flight and weather scenarios are designed to test UPR methods and assess user preferred routes provided by these methods. Third, a segment based simulation environment is developed to simulate any type of route segment (climb, cruise, or descent). The simulation uses point mass model of aircraft, and is implemented in a continuous environment, as well as in a fast time mode. This simulation environment is applied effectively and flexibly to evaluate UPR. The impact of different emissions on the environment is measured effectively. I developed a real time flight data management system with algorithms to process, estimate, and integrate information for every flight in the airspace and to construct flight objects. Then another real time system is developed to estimate aviation emission using the flight objects provided by the flight data management system. The aviation emission is stored in 4-D database to analyse the impact of aviation emission on the environment. A number of models for emissions analysis are designed and implemented. The models developed here are then used for the calculation and analysis of fuel and emissions for UPR routes. I demonstrate that, if UPR routes that have been optimised either vertically or horizontally, they can help to reduce on average about 3% and 2% fuel burn in comparison with the original flight plans respectively. If UPR routes are optimised both vertically and horizontally, they can save on average 5% fuel burn. I also demonstrate that the delay in departure times of UPR and non-UPR flights is insignificant (the average delay is less than 1 minute).