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Preference-based evolutionary algorithm for airport runway scheduling and ground movement optimisationAs airports all over the world are becoming more congested together with stricter environmental regulations put in place, research on optimisation of airport surface operations started to consider both time and fuel related objectives. However, as both time and fuel can have a monetary cost associated with them, this information can be utilised as preference during the optimisation to guide the search process to a region with the most cost efficient solutions. In this paper, we solve the integrated optimisation problem combining runway scheduling and ground movement problem by using a multi-objective evolutionary framework. The proposed evolutionary algorithm is based on modified crowding distance and outranking relation which considers cost of delay and price of fuel. Moreover, the preferences are expressed in a such way, that they define a certain range in prices reflecting uncertainty. The preliminary results of computational experiments with data from a major airport show the efficiency of the proposed approach.
Toward a more realistic, cost-effective, and greener ground movement through active routing: A multiobjective shortest path approachThis paper draws upon earlier work, which devel- oped a multiobjective speed profile generation framework for unimpeded taxiing aircraft. Here, we deal with how to seamlessly integrate such efficient speed profiles into a holistic decision- making framework. The availability of a set of nondominated unimpeded speed profiles for each taxiway segment, with respect to conflicting objectives, has the potential to significantly impact upon airport ground movement research. More specifically, the routing and scheduling function that was previously based on distance, emphasizing time efficiency, could now be based on richer information embedded within speed profiles, such as the taxiing times along segments, the corresponding fuel consumption, and the associated economic implications. The economic implica- tions are exploited over a day of operation, to take into account cost differences between busier and quieter times of the airport. Therefore, a more cost-effective and tailored decision can be made, respecting the environmental impact. Preliminary results based on the proposed approach show a 9%–50% reduction in time and fuel respectively for two international airports: Zurich and Manchester. The study also suggests that, if the average power setting during the acceleration phase could be lifted from the level suggested by the International Civil Aviation Organization, ground operations may simultaneously improve both time and fuel efficiency. The work described in this paper aims to open up the possibility to move away from the conventional distance-based routing and scheduling to a more comprehensive framework, capturing the multifaceted needs of all stakeholders involved in airport ground operations.