计算机与现代化 ›› 2012, Vol. 1 ›› Issue (1): 1-5.doi: 10.3969/j.issn.1006-2475.2012.01.001

• 人工智能 •    下一篇

基于遗传算法的动态航班着陆调度优化

冯兴杰1，孟 欣2   

  1. 1.中国民航大学教务处，天津 300300；2.中国民航大学计算机科学与技术学院，天津 300300
  • 收稿日期:2011-08-17 修回日期:1900-01-01 出版日期:2012-01-10 发布日期:2012-01-10

Scheduling Optimization of Dynamic Flight Landing Based on Genetic Algorithm

FENG Xing-jie1, MENG Xin2   

  1. 1. Office of Academic Affairs, Civil Aviation University of China, Tianjin 300300, China;2. School of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China
  • Received:2011-08-17 Revised:1900-01-01 Online:2012-01-10 Published:2012-01-10

被引次数

1

摘要： 动态航班调度是指当待调度的航班队列发生改变时，能够及时更新调度方案，这就要求排序算法在动态运行时能够产生稳定的排序结果。本文针对遗传算法在多次运行中结果不稳定的问题，提出一种基于MPS(Maximum Position Shift)约束的改进遗传算法(Genetic Algorithm，GA)，有效地避免算法早熟收敛，提高搜索效率。实验结果表明，该算法能够稳定地获得优化解。

关键词: 遗传算法, 动态航班着陆调度, 最大位置偏移, 罚函数, 全局寻优

Abstract: Dynamic flight scheduling means updating scheduling scheme timely, when the queue of the flight to be scheduled changes. This requires that scheduling algorithm should obtain stable sort results. An improved genetic algorithm based on MPS restriction is proposed to solve the problem that the results of GA aren’t stable. It can avoid effectively the situation of premature convergence and improve efficiency of search. The results show that the scheduling algorithm can get stably the optimal solution.

Key words: genetic algorithm, dynamic flight landing scheduling, maximum position shift, penalty function, global optimization solution

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