Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm
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Abstract:
Air route network (ARN) planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation. Here, the ARN shortest path was taken as the objective function, and an air route network node (ARNN) optimization model was developed to circumvent the restrictions imposed by ″three areas ″, also known as prohibited areas, restricted areas, and dangerous areas (PRDs), by creating a grid environment. And finally the objective function was solved by means of an adaptive ant colony algorithm (AACA). The A593, A470, B221, and G204 air routes in the busy ZSHA flight information region, where the airspace includes areas with different levels of PRDs, were taken as an example. Based on current flight patterns, a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs. The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.
Wang Shijin*, Li Qingyun, Cao Xi, Li Haiyun. Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm[J]. Transactions of Nanjing University of Aeronautics & Astronautics,2016,33(4):469-478