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Application of ant colony algorithm in the simulation-based approach to improve airport surface operations

机译:蚁群算法在基于仿真的改进机场地面运行方法中的应用

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摘要

In this paper, we apply the ant colony algorithm in the optimiser for the simulation-based optimisation approach to improve airport surface operations. The major components of the system architecture and detailed descriptions of the implementations of the ant colony algorithm are introduced. The proposed ant colony algorithm and the simulation-based optimisation approach are applied to the case studies of the east side of the Dallas-Fort Worth airport (DFW). The initial results have demonstrated the success and benefit of applying the ant colony algorithm in the simulation-based approach for improving airport surface operations. The results have also implied that applying the combined genetic algorithm and ant colony algorithm in the optimiser can derive better results than using any one of the two algorithms solely.
机译:在本文中,我们将优化算法中的蚁群算法应用于基于仿真的优化方法,以改善机场水面运营。介绍了系统架构的主要组成部分和蚁群算法实现的详细说明。提出的蚁群算法和基于仿真的优化方法被应用于达拉斯-沃思堡机场(DFW)东侧的案例研究。初步结果证明了在基于模拟的方法中应用蚁群算法来改善机场水面运行的成功和好处。结果还暗示,与单独使用两种算法中的任何一种相比,将遗传算法和蚁群算法结合使用在优化器中可以获得更好的结果。

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