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Multi-obj ective Collaborative Optimization for Scheduling Aircraft Landing on Closely Spaced Parallel Runways Based on Genetic Algorithms

机译:基于遗传算法的飞机近距离平行跑道着陆调度多目标协同优化

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摘要

A scheduling model of closely spaced parallel runways for arrival aircraft was proposed,with multi-ob-j ections of the minimum flight delay cost,the maximum airport capacity,the minimum workload of air traffic con-troller and the maximum fairness of airlines′scheduling.The time interval between two runways and changes of aircraft landing order were taken as the constraints.Genetic algorithm was used to solve the model,and the model constrained unit delay cost of the aircraft with multiple flight tasks to reduce its delay influence range.Each obj ec-tive function value or the fitness of particle unsatisfied the constrain condition would be punished.Finally,one do-mestic airport hub was introduced to verify the algorithm and the model.The results showed that the genetic algo-rithm presented strong convergence and timeliness for solving constraint multi-obj ective aircraft landing problem on closely spaced parallel runways,and the optimization results were better than that of actual scheduling.
机译:提出了一种紧凑的进近飞机平行跑道排班模型,该模型具有以下几方面的目标:最小的航班延误成本,最大的机场容量,最小的空中交通管制员工作量以及最大的航空公司调度公平性。将两个跑道之间的时间间隔和飞机降落顺序的变化作为约束条件,使用遗传算法求解该模型,该模型约束了具有多个飞行任务的飞机的单位延误成本,以减小其延误影响范围。最后,引入一个国内机场枢纽对算法和模型进行验证。结果表明,遗传算法具有很强的收敛性和收敛性。解决近距离平行跑道约束多目标飞机着陆问题的时效性,优化结果优于实际计划尤灵

著录项

  • 来源
    《南京航空航天大学学报(英文版)》 |2016年第4期|502-509|共8页
  • 作者单位

    College of Civil Aviation,Nanjing University of Aeronautics and Astronautics, Nanjing 211106,P.R.China;

    College of Civil Aviation,Nanjing University of Aeronautics and Astronautics, Nanjing 211106,P.R.China;

    College of Civil Aviation,Nanjing University of Aeronautics and Astronautics, Nanjing 211106,P.R.China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 跑道、滑行道、停机坪;
  • 关键词

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