基于改进蚁群协同算法的枢纽机场场面滑行道优化调度模型

计算机应用 ›› 2010, Vol. 30 ›› Issue (4): 1000-1003.

基于改进蚁群协同算法的枢纽机场场面滑行道优化调度模型

丁建立¹,李晓丽²,李全福¹

1.
2. 中国民航大学计算机学院

收稿日期:2009-10-30 修回日期:2009-12-06 发布日期:2010-04-15 出版日期:2010-04-01
通讯作者: 李晓丽
基金资助:
国家高技术研究发展计划(863);国家自然科学基金资助项目;国家自然科学基金资助项目

Optimal scheduling model for hub airport taxi based on improved ant colony collaborative algorithm

Received:2009-10-30 Revised:2009-12-06 Online:2010-04-15 Published:2010-04-01
Contact: Li XiaoLi

摘要/Abstract

摘要： 滑行道连接停机位和跑道，是机场场面调度的重要关键环节。基于飞机滑行时的冲突约束和跑道资源的动态分配，采用改进蚁群协同算法与滑动窗口控制相结合的方法，对滑行道进行优化调度。在保证滑行道零冲突、兼顾单个航班滑行时间的前提下，缩小机场进出港航班总滑行时间。对国内某枢纽机场的滑行道调度仿真实验表明，所提出的方法和模型具有明显的优势，可为枢纽机场的场面滑行调度提供决策支持。

关键词: 滑行道调度, 蚁群协同算法, 滑动窗口控制, 枢纽机场跑道

Abstract: Taxiway connects parking spot and runway, which takes an important part in airport surface scheduling. According to the constraints of aircraft taxi conflict and dynamic allocation of runway’s resources, improved ant colony collaborative algorithm and sliding window control were adopted to optimize taxi scheduling. Ensuring taxi conflict free and taking account of single flight taxi time, total taxi time of inbound and outbound flights was reduced. A domestic hub airport taxi scheduling simulation shows that the proposed method and model have obvious advantages, which can provide decision support for hub airport’s taxi scheduling.

Key words: taxiway scheduling, ant colony collaborative algorithm, sliding window control, hub airport runway

丁建立李晓丽李全福. 基于改进蚁群协同算法的枢纽机场场面滑行道优化调度模型[J]. 计算机应用, 2010, 30(4): 1000-1003.