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Optimization of Air Route Network Nodes to Avoid″Three Areas″Based on An Adaptive Ant Colony Algorithm

机译:基于自适应蚁群算法的避免“三个区域”的航线网络节点优化

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摘要

Air route network (ARN)planning is an efficient way to alleviate civil aviation flight delays caused by in-creasing 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 crea-ting a grid environment.And finally the obj ective 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%.
机译:空中路线网络(ARN)规划是减轻由危险开发和安全操作压力引起的民用航空飞行延误的有效方法。,ARN最短路径作为目标函数,以及空路网络节点(ARNN )开发了优化模型,以规避“三个区域”,也称为禁止区域,限制区域和危险区域(PRD),通过CREA-TIT-TIF-TIFINATE来规避禁止区域,限制区域和危险区域自适应蚁群算法(AACA)。繁忙ZSHA飞行信息区域A593,A470,B221和G204空中路线,其中空域包括不同级别的PRD水平的区域。基于当前飞行模式,使用该模型和算法计算ARNN的布局优化,并成功避免了PRD。优化结果将路线的总长度降低2.14%,总成本为9.875%。

著录项

  • 来源
    《南京航空航天大学学报(英文版)》 |2016年第4期|469-478|共10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;

    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 U8;
  • 关键词

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