| Airport gates are regarded as an important resource. Using limited resources in airport gates, it is an important scheme to allocate aircrafts, in order to provide a better service for arrival and departure of aircrafts. The allocation of airport gates are defined as follows:in consideration of the sizes of aircrafts, types of parking area, flight schedules and other factors, a suitable airport gates assignment should be provided for the aircraft in the near future. Meanwhile, services should be provided for boarding passengers, and the scheduled flight must be in proper operation. A reasonable airport gates assignment is very important for developing the efficiency of airport and decreasing flight delay.In this thesis, an improved SWO algorithm for AGAP was proposed, in which a Tabu Search Method was incorporated to optimize the allocations of airport gates. First, using shortest walking length of passengers as optimization objective, the SWO algorithm was developed to solve the airport gates assignment problem. Experiments were carried out to validate this approach. Second, the SWO algorithm searched into two different spaces simultaneously. A small change in the order of components might lead to large change in the solutions. In order to improve the performance, a Tabu Search was incorporated into SWO algorithm. Compared with the conventional SWO algorithm, experimental results show that the efficiency and execution speed were improved. Third, the improved SWO algorithm was also compared with the Genetic Algorithm. The solutions were compared by using the improved SWO algorithm and Genetic Algorithm. The results show that a higher convergence rate and quality solutions were obtained by using the improved SWO algorithm than those obtained by using Genetic Algorithm. |
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