成本约束下多机场群航班频率优化模型仿真  

Simulation of Multi-Airport Group Flight Frequency Optimization Model under Cost Constraints

作　　者：韦薇[1] 何晶 WEI Wei;HE Jing(College of Air Transport,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学航空运输学院,上海201620

出　　处：《计算机仿真》2022年第6期31-35,共5页Computer Simulation

基　　金：国家社科基金一般项目(15BJL104)。

摘　　要：采用目前方法对多机场群航班频率进行优化时,没有考虑旅客的出行成本,对航班频率优化后存在延误时间长、延误航班数量多、出行成本高和日利用率低的问题。提出考虑出行成本的多机场群航班频率优化模型构建方法,在构建航班频率优化模型之前,对旅客的出行方式进行博弈分析,在Stackelberg博弈模型的基础上构建双层博弈模型,上层模型实现社会效益最大化,下层模型实现旅客出行费用最小化,完成多机场群航班频率优化模型的构建,并采用遗传算法对多机场群航班频率优化模型求解,完成航班频率的优化。仿真结果表明,所提方法的延误时间短、延误航班数量少、出行成本低、日利用率低。When the traditional method optimizes the flight frequency of multi-airport groups, there are many defects, such as long delay time, many delayed flights, high travel costs and low daily utilization rate, being caused by the neglect of passenger travel costs. Therefore, this paper reports a construction method of the multi-airport group flight frequency optimization model based on travel cost. Before the flight frequency optimization model was constructed, the game analysis of passengers’ travel mode was completed. Based on the Stackelberg game model, a two-level game model was constructed. The upper model aims at the highest social benefit, while the lower model aims at the lowest passenger travel cost. The multi-Airport Group flight frequency optimization model was established, and the model was solved by a Genetic Algorithm. Eventually, the flight frequency optimization was completed. The simulation results show that this method has a short delay time, fewer delayed flights, low travel costs and utilization.

关 键 词：出行成本 多机场群 航班频率优化 双层博弈模型 遗传算法 

分 类 号：V352[航空宇航科学与技术—人机与环境工程]