| 基于行程多路径的航空公司航班频率优化 |
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| 引用本文： | 乐美龙,郑文娟,胡钰明.基于行程多路径的航空公司航班频率优化[J].交通运输工程学报,2020,20(5):217-226. |
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| 作者姓名： | 乐美龙 郑文娟 胡钰明 |
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| 作者单位： | 1.南京航空航天大学 民航学院, 江苏 南京 2100162.中国民航工程咨询有限公司, 北京 1013003.中南民航空管通信网络科技有限公司, 广东 广州 510403 |
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| 基金项目： | 江苏省自然科学基金;国家自然科学基金 |
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| 摘 要： | 将航空运输网络抽象为多层级网络结构, 构建了确定航空公司某一城市对某条路径航班频率的两阶段规划模型: 第一阶段从旅客选择行为的角度, 考虑旅客对旅行时间、过站时间、计划延误时间、票价等因素的价值感知, 构建旅客旅行负效用函数, 进而基于多项式Logit模型构建计算旅客选择某个航空公司某个城市对某条路径概率的旅客路径选择模型; 第二阶段从航空公司的角度, 以总收益最大化为目标函数, 基于行程多路径, 并考虑航空公司总运力限制, 尽可能地让每条路径的运力供给等于需求, 构建了确定路径航班频率的线性规划模型; 提出了求解两阶段模型的迭代算法。研究结果表明: 提出的算法能够在8次迭代之后达到收敛, 可以在较短的时间内得到最优解; 随着算法的收敛, 构建的两阶段规划模型在航线存在市场竞争且整体运力不足的情况下优先将运力安排到收益最高的航线上, 提升航空公司整体收益; 对于包含多个航节的航线, 构建的两阶段模型更能体现旅客选择行为在航班频率配置中发挥的作用; 对于包含一个航节的航线, 需求随航班频率的变动幅度较小, 随着迭代次数的增加, 需求航班频率弹性系数逐渐变小, 对于包含多个航节的航线, 在航线总需求一定的情况下, 需求随航班频率的变动幅度较大, 由于市场竞争存在航班频率不变需求骤减的情形。可见, 所提出的模型和算法能够有效提升航空公司收益。
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| 关 键 词： | 航空运输 航班频率优化 路径选择 多层级网络 迭代算法 航节 |
| 收稿时间： | 2020-04-08 |
Airline flight frequency optimization based on multiple travel paths |
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| LE Mei-long,ZHENG Wen-juan,HU Yu-ming.Airline flight frequency optimization based on multiple travel paths[J].Journal of Traffic and Transportation Engineering,2020,20(5):217-226. |
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| Authors: | LE Mei-long ZHENG Wen-juan HU Yu-ming |
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| Affiliation: | 1.College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China2.China Civil Aviation Engineering Consulting Co., Ltd., Beijing 101300, China3.Middle South Civil Aviation ATC Communication Network Technology Co., Ltd., Guangzhou 510403, Guangdong, China |
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| Abstract: | A multiple-layer network was abstracted from the airline's air transport network, and a two-stage planning model was built to determine the flight frequency along a certain route by an airline for a specific city pair. In the first stage, a negative utility function of travel was constructed on the basis of the passengers' selection behavior by considering their perception of travel time, transfer time, delay time, and ticket price. Subsequently, a polynomial Logit model was adopted to create a route selection model in order to calculate the probability of passengers selecting a certain route by an airline for a specific city pair. In the second stage, a linear planning model was established to determine the flight frequency from the airline's perspective. The overall objective was to maximize the total revenue, the multiple travel paths, the total carrier capacity of the airline, and the balance between the carrier supply and demand for each path were considered. An iterative algorithm was presented to solve the proposed two-stage model. Analysis result shows that the convergence can be achieved after 8 iterations, and thus, the optimal solution can be reached within a short time. As the solutions converge, the proposed two-stage planning model prioritizes the routes with the highest revenue to improve the overall revenue in cases where there is market competition and insufficient overall capacity. For the routes with multiple segments, the two-stage model can more clearly present the role of the passengers' selection behavior related to the flight frequency determination. For the routes with only one segment, there is less variation in demand with respect to the change in the flight frequency. As the number of iterations increases, the demand tends to become decreasingly sensitive to the flight frequency. For the routes with multiple segments, the variation in the demand with change in the flight frequency is considerably higher in the cases when the total demand is fixed. Conversely, the demand decreases sharply when the flight frequency remains unchanged due to the market competition. Therefore, the presented model and algorithm can effectively improve the airline revenue. |
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