基于蚁群算法的多跑道航班协同调度建模  

Modeling of Collaborative Scheduling of Flights on Multi-Runways Based on Ant Colony Algorithm

作　　者：徐兆龙[1] 姜雨[1] 罗宇骁[1] 徐新星[1] 

机构地区：[1]南京航空航天大学民航学院,南京210016

出　　处：《武汉理工大学学报（交通科学与工程版）》2014年第6期1362-1366,1371,共6页Journal of Wuhan University of Technology（Transportation Science & Engineering）

基　　金：国家自然科学基金项目(批准号:U1333117);国家博士后科学基金项目(批准号:2012M511275);校级基本业务经费(批准号:NS2013067)资助

摘　　要：针对终端区航班拥堵问题,模型通过读取进离场航班的航班号、机型和所属航空公司等实时信息,以提高航空公司效益性和航空公司之间竞争公平性为目标,建立了多跑道航班协同调度(CDM GDP)的多目标动态优化模型,采用蚁群算法对模型进行仿真.经过仿真验证表明,模型优化算法与先到先服务(FCFS)状态下航班排序相比,延误损失降低70.10%;延误损失偏差和降低38.64%.As for the problem of flight congestion in the terminal area,by reading into the flight number,type and airlines and other real-time information of the approach and departure flights,treating the improvement of airlines＇ economic benefits and the fair competition among airlines as the objectives,a multi-objective dynamic optimization model based on multi-runways flight collaborative scheduling（CDM GDP）is established,and ant colony algorithm is used to simulate and verify.The results show that the model optimization algorithm is better than FCFS（first come first served）,which the delay losses is reduced by 70.10%,and the sum of delay losses deviation is also reduced by 38.64%.

关 键 词：空中交通管制 航班协同调度 效益性 公平性 多目标蚁群算法 

分 类 号：V351.11[航空宇航科学与技术—人机与环境工程]