Abstract
Taking into consideration the constraints and objectives to appropriately assigning the available airport resources throughout the period of time an airport provides its services can greatly affect the quality of service which airlines and airports provide to their customers. The appropriate assignments can help airlines and airports to keep to published schedules, by minimising changes in these schedules, reducing delays and considering customers preferences when assigning the resources. Given the expected increases in civil air traffic, and the variety of resources, the complexities of resource scheduling and assignment continue to increase. For this reason, as well as the dynamic nature of the problems, scheduling and assignment are becoming increasingly more difficult. An Evolutionary Algorithm is presented together with some different operators, which are used to find good solutions to the Airport Baggage Sorting Station Assignment Problem for when there are not sufficient resources up to when the number of resources is sufficient to fulfil the demand on these resources. The contributions of these different operators are studied and compared to other approaches, giving insights into how the appropriate choice may depend upon the specifics of the problem at the time.
Highlights
Many airport resources are of limited availability and are expensive or time-consuming to increase in quantity
The algorithms described are applied to the Airport Baggage Sorting Station Assignment Problem (ABSSAP) for different number of baggage sorting station (BSS) and stands, and their results are compared and analysed for both the data sets obtained from British Airports Authority (BAA)’s website and those provided by NATS Ltd. for Heathrow Airport London
The empirical results for the Steady-State Evolutionary Algorithm (SSEA) show that this algorithm performs better than the other algorithms considered, which suggests a potential application to the problem under consideration as well as other resource assignment problems such as the Airport Gate Assignment Problem (AGAP)
Summary
Many airport resources (for example, stands, gates, tugs, storage points, fuel trucks and baggage stations) are of limited availability and are expensive or time-consuming to increase in quantity. Many approaches have been used to solve optimisation problems, like the Airport Baggage Sorting Station Assignment Problem (ABSSAP), two of which are Genetic Algorithms (GAs) and Tabu Search (TS). Various different ABSSAP objectives have to be considered, such as maximising assignments, ensuring full service time and allocating preferential positions. Some of these objectives are in obvious conflict (reducing service times in order to service an additional flight, for example), preventing simultaneous optimisation of each objective. The following sections begin by a description of the problem, followed by a description of the proposed EA with its operators and selectors, followed by a study of the problem, using a fitness function as a single compound objective which represents realistic priorities
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