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Multirunway Optimization Schedule of Airport Based on Improved Genetic Algorithm by Dynamical Time Window

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  • Hang Zhou
  • Xinxin Jiang

Abstract

Reasonable airport runway scheduling is an effective measure to alleviate air traffic congestion. This paper proposes a new model and algorithm for flight scheduling. Considering the factors such as operating conditions and flight safety interval, the runway throughput, flight delays cost, and controller workload composes a multiobjective optimization model. The genetic algorithm combined with sliding time window algorithm is used to solve the model proposed in this paper. Simulation results show that the algorithm presented in this paper gets the optimal results, the runway throughput is increased by 12.87%, the delay cost is reduced by 61.46%, and the controller workload is also significantly reduced compared with FCFS (first come first served). Meanwhile, compared with the general genetic algorithm, it also reduces the time complexity and improves real-time and work efficiency significantly. The analysis results can provide guidance for air traffic controllers to make better air traffic control.

Suggested Citation

  • Hang Zhou & Xinxin Jiang, 2015. "Multirunway Optimization Schedule of Airport Based on Improved Genetic Algorithm by Dynamical Time Window," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-12, October.
    • Handle: RePEc:hin:jnlmpe:854372
    DOI: 10.1155/2015/854372
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    Cited by:

    1. Sun, Chunhua & Chen, Jiali & Cao, Shanshan & Gao, Xiaoyu & Xia, Guoqiang & Qi, Chengying & Wu, Xiangdong, 2021. "A dynamic control strategy of district heating substations based on online prediction and indoor temperature feedback," Energy, Elsevier, vol. 235(C).

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