双交叉算子遗传算法在终端区飞机排序中的应用

当今，普遍的航班延误现象不仅增加了巨额飞行成本，还影响乘客体验. 对终端区待降飞机队列进行合理调整，可以提高跑道利用率，减少航班延误，达到降低延误代价的效果. 针对终端区飞机排序问题，提出一种包含双交叉算子的遗传算法，针对不同适应度染色体采取不同的交叉操作，使得在交叉过程中既能保护优质染色体，也能使其它染色体继续进化. 同时引入重排算子对变异后的子代进行优化，共同加快遗传算法收敛速度，使其更加符合实际使用需求. 实验结果表明，算法收敛速度得到改进，能在可接受时间内得到可行解.

Application of Double Crossover Operator Genetic Algorithm to Aircraft Sequencing in Terminal Area

Nowadays, the widespread phenomenon of flight delays does not only increase massive flight costs, but also impacts the experience of passengers. Reasonably adjusting the aircraft queue in terminal areas can raise the utilization ratio of the runway and reduce flight delays. Finally, the cost of delay can be cut down. To resolve the problem of aircraft scheduling in terminal areas, this article puts forward an genetic algorithm including double crossing operator. Different crossover operations are carried out for chromosomes with different fitness so that the quality of chromosomes can be protected and the others continue to evolve. At the same time, reordering operator is introduced to optimize the descendants after mutation to improve convergence rate of genetic algorithm and makes it more suitable for practical use. The experimental results show that the convergence rate of algorithm is improved and the feasible solution can be obtained within acceptable time.