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摘要: 为了保障飞行安全, 对终端区着陆飞机进行有效的排序, 建立了以航班延误总时间最小为目标函数的规划模型, 以人工鱼群算法为基础, 融合了遗传算法的选择操作和模拟退火算法的依概率接受的思想, 形成混合人工鱼群算法, 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、模拟退火算法以及蚁群算法进行了对比研究。仿真结果表明: 与先到先服务相比, 使用人工鱼群算法使得单跑道、双跑道延误分别减少了9.3%和48.0%, 计算时间小于3s;与蚁群算法和模拟退火算法相比, 求解的延误与时间最小, 因此, 提出的混合算法可行。Abstract: In order to ensure flight safety and effectively sequence landing aircrafts in terminal area, an object model with minimum total delay was developed, the ideas of selection operation in genetic algorithm (GA) and the acceptance according to probability in simulated annealing (SA) algorithm were considered, a mixed algorithm was proposed based on artificial fish school algorithm (AFSA), 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 9.3% and 48.0% for single and double runways compared with FCFS algorithm, computational time is less than 3 s, while the delay and computational time are least compared with SA algorithm and ant colony optimization algorithm, so the mixed algorithm (MA) is feasible.
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Key words:
- air traffic control /
- flow management /
- AFSA /
- aircraft sequencing /
- terminal area
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表 1 单跑道排序仿真结果
Table 1. Sequencing simulation results at single runway
飞机代码 FCFS MA E (i) /min S (i) /min E (i) /min S (i) /min HC2 6.0 6.0 6.0 6.0 HC3 6.0 7.0 6.0 7.0 HC7 6.0 8.0 6.0 8.0 HC8 6.0 9.0 6.0 9.0 HC5 7.0 10.0 7.0 10.0 SC4 9.0 12.0 9.0 13.0 SC9 9.0 13.0 9.0 14.0 HC0 11.0 14.0 11.0 11.0 LC1 15.0 15.5 15.0 15.0 LC6 15.0 17.0 15.0 16.5 总延误/min 21.5 19.5 
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表 2 双跑道排序仿真结果
Table 2. Sequencing simulation results at double runways
FCFS MA 跑道1 跑道2 跑道1 跑道2 代码 E* (i) /min S (i) /min 代码 E* (i) /min S (i) /min 代码 E* (i) /min S (i) /min 代码 E* (i) /min S (i) /min HC2 6.0 6.0 HC5 6.0 6.0 HC2 6.0 6.0 HC5 6.0 6.0 HC3 6.0 7.0 HC0 10.0 10.0 HC3 6.0 7.0 HC7 6.0 7.0 HC7 6.0 8.0 总延误为12.5 min SC4 9.0 9.0 HC8 6.0 8.0 HC8 6.0 9.0 SC9 9.0 10.0 HC0 10.0 10.0 SC4 9.0 11.0 LC1 15.0 15.0 总延误为6.5 min SC9 9.0 12.0 LC6 15.0 16.5 LC1 15.0 15.0 LC6 15.0 16.5
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表 3 算法仿真性能比较
Table 3. Comparison of simulation performances for 4 algorithms
单跑道 双跑道 算法 最优解/min 最差解/min 平均解/min 平均计算时间/s 最优解/min 最差解/min 平均解/min 平均计算时间/s FCFS 21.5 21.5 21.5 0.396 12.5 12.5 12.5 0.988 ACO 19.5 21.5 19.5 2.850 6.5 9.0 7.0 3.165 SA 19.5 23.5 21.5 0.697 7.0 23.5 10.5 12.398 MA 19.5 19.5 19.5 0.667 6.5 7.0 6.5 2.084
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