终端区飞机排序的人工蜂群算法

摘 要：为缓解终端区空中交通压力，研究了人工蜂群算法在终端区飞机降落排序中的应用。建立以航班总延误时间最小为目标函数的规划模型，运用人工蜂群算法，对着陆飞机排序问题进行了仿真计算，并与先到先服务算法、模拟退火算法、蚁群算法进行了对比研究。仿真结果表明：在双跑道模型下，人工蜂群算法比先到先服务算法，延误减少了48%。与模拟退火算法和蚁群算法相比，人工蜂群算法求解的结果最优且用时最少。说明应用人工蜂群算法求解终端区飞机排序问题是可行的。

Artificial bee colony algorithm of aircraft sequencing in terminal area

Abstract: In order to relieve air traffic pressure, this paper applied the artificial bee colony algorithm (ABC) to study sequencing and scheduling of landing aircraft in the terminal area. An object model with minimum total delay was developed. The sequence problem of landing aircraft was solved, and its computational result was compared with the ones computed by first-come-first-serve (FCFS) algorithm, SA algorithm and ant colony optimization (ACO) algorithm. Simulation result shows that the total delays are respectively reduced by 48% for double runways compared with FCFS algorithm, while the delay and computational time are least compared with SA algorithm and ACO algorithm, so the ABC algorithm is feasible to solve the aircraft sequencing problem in terminal area.