基于蚁群算法的多跑道航班协同调度建模

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%.

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

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%.