Volume 39 Issue 2
Apr.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(2): 109-117
ZHU Chengyuan, YAN Nanxin. A Simulation Optimization Algorithm for Multi-aircraft Rerouting in Severe Weather[J]. Journal of Transport Information and Safety, 2021, 39(2): 109-117. doi: 10.3963/j.jssn.1674-4861.2021.02.014
Citation: ZHU Chengyuan, YAN Nanxin. A Simulation Optimization Algorithm for Multi-aircraft Rerouting in Severe Weather[J]. Journal of Transport Information and Safety, 2021, 39(2): 109-117. doi: 10.3963/j.jssn.1674-4861.2021.02.014
shu

A Simulation Optimization Algorithm for Multi-aircraft Rerouting in Severe Weather

doi: 10.3963/j.jssn.1674-4861.2021.02.014

  • College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China

  • Received Date: 2021-01-24
    Abstract
  • A simulation optimization algorithm for multiple aircraft diversion routes under severe weather is studied to address the lack of consideration for reducing the total controller workload in the planning of multiple aircraft re-routes in the regional control area(RCA)during severe weather. Guiyang RCA is taken as a case study. A gray model is used to predict the dynamic impact range of the flight forbidden area(FFA), and a geometric algorithm is used to plan the alternative diversion routes, with the operation rules of the discrete particle swarm optimization algorithm (DPSO)improved. The simulation optimization algorithm of multiple aircraft diversion routes in severe weather is implemented by combining the predicted FFA, the pre-planned diversion routes, the improved DPSO algorithm, and the total airspace and airport modeler(TAAM)to minimize the total diversion routes and the total controller workload in the whole area. The results show that the simulation optimization algorithm, after several iterations, can obtain a diverting optimization scheme. The total controller workload decreases by 7.52%, and the total distance of diverting routes decreases by 4.48%, compared with the simulation optimization algorithm using the traditional particle swarm optimization algorithm(PSO). It has a slightly longer distance of diverting routes compared with the rerouting path algorithm using the multi-objective particle swarm algorithm(MOPSO)and the non-dominated sorted genetic algorithm-II(NSGA-II). However, the influences of controller workload should be considered. The simulation optimization algorithm can reduce the effective controller workload and the distance of diverting routes, which is useful for the planning of actually diverting routes.

     

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