一种机场终端区飞机排序问题的蚁群算法研究

山东大学学报(工学版)

一种机场终端区飞机排序问题的蚁群算法研究

陈欣¹，　杨文东¹，　陆迅^1,2，　朱金福¹

1. 南京航空航天大学民航学院，江苏南京210016；2. 上海机场战略部，上海201206

收稿日期:2007-04-16 修回日期:1900-01-01 出版日期:2007-12-24 发布日期:2007-12-24
通讯作者: 陈欣

An ant colony algorithm for an aircraft sequencing problem in the airport terminal area

CHEN Xin¹,YANG Wen-dong¹,LU Xun^1,2,ZHU Jin-fu¹

1. School of Civil Aviation，Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu,China;2. Department of Strategy and Development,Shanghai Airport Authority

Received:2007-04-16 Revised:1900-01-01 Online:2007-12-24 Published:2007-12-24
Contact: CHEN Xin

摘要/Abstract

摘要： 飞机排序问题（ASP）属于NP难问题，解决比较困难.本文首先将ASP表示成一个特殊的车间作业调度问题（JSP），以减少着陆飞机队列完成时间为优化目标，设计了求解ASP的蚁群算法.通过正交试验确定了ASP蚁群算法的最佳性能参数组合.通过比较FCFS调度方法和ASP蚁群算法对不同航班队列的排序结果验证了ASP蚁群算法求解问题的可行性和求解效果.结果表明，ASP蚁群算法优于FCFS调度方法，可以使着陆队列完成时间减少约14%.ASP蚁群算法的CPU时间较短，可以在合理的时间内求解出合适的飞机队列，为实时在线的自动化交通管制提供了支持.

关键词: 蚁群算法, 飞机排序问题, FCFS, 车间作业调度问题, 机场终端区, 空中交通管理

Abstract: Aircraft sequencing problem (ASP) is a non-deterministic polynomial hard (NPhard) problem, which is hard to resolve. The ASP is treated as a particular job-shop scheduling problem (JSP), and an ant colony algorithm(ACA) for ASP is designed with the objective of minimizing the makespan of landing airplanes. The orthogonal test is employed to study the optimal parameters of ACA for ASP. The efficiency and reliability of ACA for ASP is investigated by comparing with the sequencing results of FCFS method for different numbers of landing aircrafts. The ACA for ASP is proved to be better than FCFS, which can decrease the makespan of landing airplanes by 14%. The ACA of ASP can obtain a satisfied solution with shorter CPU time, which can provide support for the realtime automatic air traffic management.

Key words: ant colony algorithm, aircraft sequencing problem, FCFS, job-shop scheduling problem, airport terminal area, air traffic management

中图分类号:

V351.11

陈欣,杨文东,陆迅,朱金福 . 一种机场终端区飞机排序问题的蚁群算法研究[J]. 山东大学学报(工学版), 2007, 37(6): 111-117 .

CHEN Xin,YANG Wen-dong,LU Xun,ZHU Jin-fu . An ant colony algorithm for an aircraft sequencing problem in the airport terminal area[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2007, 37(6): 111-117 .

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