工业工程

工业工程 ›› 2015, Vol. 18 ›› Issue (5): 122-126.

• 实践与应用 • 上一篇    下一篇

基于轮辐式航线网络的航班舱位控制动态优化

  

  1. （1.上海海事大学 经济管理学院 上海 201306； 2.南京航空航天大学 民航学院，江苏 南京 211106）
  • 出版日期:2015-10-31 发布日期:2016-03-24
  • 作者简介:高金敏（1990-），女，山东省人，博士研究生，主要研究方向为交通运输系统优化
  • 基金资助:

    国家自然科学基金资助项目（71471110）；江苏省自然科学基金资助项目（BK20151479）

A Dynamic Optimization Research of Flight Seat Inventory Control Based on the Hub and Spoke Route Network

  1. （1. School of Economics and Management, Shanghai Maritime University, Shanghai 201306，China;2. College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 211106，China）
  • Online:2015-10-31 Published:2016-03-24

摘要： 为使航班舱位控制更贴近旅客实际订座需求，有效提高航空公司收益，基于轮辐式航线网络结构的特点，从航班实际运行的角度出发，同时考虑需求的不确定性以及动态性，建立舱位控制动态优化模型。通过模拟仿真得到各订座阶段旅客随机到达数量，运用遗传算法求得各航班舱位等级的座位保护数，根据票价价值进行等级嵌套。结果表明，该方法与单独使用遗传算法的舱位控制方法相比较，能将总收益提高2.35%，具有一定的参考意义。

关键词: 轮辐式航线网络, 舱位控制, 遗传算法, 等级嵌套

Abstract: To keep the seat inventory control closer to actual passenger reservation demand, and effectively improve airline revenue, a dynamic optimization model of seat inventory control is established based on the characteristics of the hub and spoke route network, from the perspective of practical operation, considering demand uncertainty and dynamics at the same time. The random arrival passenger number of different reservation phases is obtained by simulation, the number of seats to protect each flight segment is obtained by using genetic algorithm, and the nested grade is obtained according to the fare value. The running results show that this method can increase the total revenue by 2.35% compared with the method using genetic algorithm only. It has certain reference significance.

Key words: hub and spoke route network, the seat inventory control, genetic algorithm, nested grade 