期刊文献+

基于改进区域生长算法的终端区扇区优化 被引量:3

Terminal Area Sector Operation Optimization Based on Improved Region Growing Algorithm
下载PDF
导出
摘要 针对民航业发展中空中交通流量不断增加以及空域划分不合理导致的流量分布、管制员负荷分布不均等问题,基于空中交通管制扇区划分的思想,对终端区扇区优化算法进行了研究。通过对终端区空域实际交通流网络进行数学描述,利用流量栅格矩阵划分空域单元,并以航迹数据作为统计依据建立扇区优化的数学模型,实现利用流量数据代替负荷计算,简化了扇区优化的过程。针对传统生长算法所得扇区不连续空域较多问题,提出环形生长的改进区域生长算法得到最优的扇区划分。最终,以厦门终端区为例,通过改进区域生长算法所得的扇区管制员负荷,经计算均小于总时间的80%,且最小负荷差为304 s,验证了所提出扇区优化方法的合理性。 With increasing air traffic flow and uneven distribution of flow and controller workload caused by unreasonable airspace division, the air traffic control sector division has been a significant means to cope with growing demand of terminal airspace. This paper presents a terminal sector optimization algorithm. With the description of the actual transportation network of terminal airspace, partition the airspace units in traffic grid matrix and track data as the statistical basement, a mathemat- ics model of sector optimization is built which simplifies sector optimization greatly. Due to the discontinuity of sector airspace resulted by the traditional growing algorithm, this paper proposes the improved region growing algorithm for optimum sector, At last, an example of Xiamen terminal sector optimum is given, which shows the reasonableness of the proposed optimization methods based on controller workload. Workload of every sector is equally less than 80% of total time and the minimum differentiation is 304s.
作者 戴福青 王丹
出处 《中国民航飞行学院学报》 2017年第3期14-18,共5页 Journal of Civil Aviation Flight University of China
关键词 扇区划分 改进区域生长算法 终端区 管制员负荷 Sector division Improved region growing algorithm Terminal airspace Controller workload
  • 相关文献

参考文献2

二级参考文献11

  • 1Tofukuji N.An enroute ATC simulation experiment for sector capacity estimation [A].IEEE Transactions on Control Systems Technology[C].New York:IEEE,1993.
  • 2Delahaye D,Schoenauer M,Alliot J M.Airspace sectoring by evolutionary computation[A].Proceeding of 10th IEEE Conference on Artificial Intelligence for Applications [C].New York:IEEE,1998.
  • 3Delahaye D,Alliot J M,Schoenauer M,et al.Genetic algorithms for partitioning airspace[A].Proceeding of 10th IEEE Conference on Artificial Intelligence for Applications[C].New York:IEEE,1994.
  • 4Tofukuji N. An enroute ATC simulation experiment for sector capacity estimation[A]. IEEE Transactions on Control Systems Technology[C]. IEEE USA, 1993.138~143.
  • 5Delahaye D,Schoenauer M,Alliot J M.Airspace sec-toring by evolutionary computation[A]. Proc of 10th IEEE Conference on Artificial Intelligence for Applications[C]. IEEE,USA:New York,1998.218~223.
  • 6Delahaye D, Odoni A. Airspace congestion smoot-hing by stochastic optimization[A]. Proceedings of the sixth International Conference on Evolutionary Programming[C]. IEEE USA, 1997.163~176.
  • 7Delahaye D, Alliot J M, Schoenauer M, et al. Ge-netic algorithms for partitioning airspace[A]. Proc of 10th IEEE Conference on Artificial Intelligence for Applications[C]. IEEE, USA: Los Alamitos, 1994.291~297.
  • 8Delahaye D, Alliot J M, Schoenauer M, et al. Ge-netic algorithms for air traffic assignment[A]. Proceedings of the Conference on Artificial Intelligence Application[C]. UK: Chichester, Cohn, A G, 1994. 33~37.
  • 9谢云.模拟退火算法的原理及实现[J].高等学校计算数学学报,1999,21(3):212-218. 被引量:37
  • 10杨庆之.无约束优化问题模拟退火算法的改进[J].高等学校计算数学学报,2001,23(2):108-110. 被引量:2

共引文献13

同被引文献32

引证文献3

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部