系统仿真学报 ›› 2016, Vol. 28 ›› Issue (3): 620-626.

• 仿真应用工程 • 上一篇    下一篇

基于改进遗传算法的飞机排班优化方法研究

李耀华, 王磊   

  1. 中国民航大学航空工程学院,天津 300300
  • 收稿日期:2014-10-26 修回日期:2015-01-16 发布日期:2020-07-02
  • 作者简介:李耀华(1974-),男,山西原平,博士,副教授,研究方向为复杂工业过程建模、生产计划与调度和智能求解算法等。
  • 基金资助:
    国家自然科学基金委员会与中国民用航空局联合资助项目(U1233107);中央高校基本科研业务费中国航大学专项(3122014C007)

Study on Aircraft Scheduling Optimization Based on Improved Genetic Algorithm

Li Yaohua, Wang Lei   

  1. Aeronautic Engineering College, Civil Aviation University of China, Tianjin 300300, China
  • Received:2014-10-26 Revised:2015-01-16 Published:2020-07-02

摘要: 针对飞机排班问题进行研究,将机型与飞机结合在一起考虑其成本和收益,并建立以综合利润最大为目标的飞机排班优化模型。在此基础上,针对该模型的特点,对遗传算法中的染色体编码形式进行创新,使其形成染色体组,在求解过程中,算法中的染色体进行交叉和变异,并且为了加快求解速度,将交叉和变异概率根据适应值作出动态调整。在利用计算机仿真的过程中,将基本遗传算法与改进的遗传算法作出对比,并采用航空公司的实际数据进行仿真,验证提出的模型和算法的可行性。

关键词: 飞机排班, 遗传算法, 染色体组, 计算机仿真

Abstract: Aircraft scheduling was studied, and an optimization model of aircraft assignment based on the objective function of maximize total profit was suggested. It considered its cost and benefits by combining fleet and aircraft. In the view of the feature of this model, the innovation of genetic algorithm chromosome was carried on, and these chromosomes formatted chromosome groups. The groups interior could cross over and mutate, and the probability of crossover and mutation could dynamically adjust in accordance with adaptive values to accelerate the convergence speed, the model was resolved fast in this way. In the process of simulation with computer, comparing genetic algorithm with adaptive genetic algorithm is to confirm the feasibility of model and algorithm which used the actual data of airlines to simulate.

Key words: aircraft scheduling, genetic algorithm, chromosome group, computer simulation

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