交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (2): 289-299.DOI: 10.16097/j.cnki.1009-6744.2026.02.027

• 系统工程理论与方法 • 上一篇    下一篇

考虑飞行机组编制规模的机组配对优化方法

张宝成* ,谢亚辰   

  1. 中国民航大学,空中交通管理学院,天津300300
  • 收稿日期:2025-11-02 修回日期:2025-12-29 接受日期:2026-02-10 出版日期:2026-04-25 发布日期:2026-04-21
  • 作者简介:张宝成(1979—),男,天津人,副教授。
  • 基金资助:
    国家自然科学基金民航联合基金重点项目(U2333206);天津市教委科研计划项目(2022KJ080)。

Crew Pairing Optimization Method Considering Flight Crew Size

ZHANG Baocheng, XIE Yachen   

  1. School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
  • Received:2025-11-02 Revised:2025-12-29 Accepted:2026-02-10 Online:2026-04-25 Published:2026-04-21
  • Supported by:
    Key Project of Civil Aviation Joint Fund of National Natural Science Foundation of China(U2333206);Tianjin Education Commission Research Program Project(2022KJ080)。

摘要: 传统的两阶段求解机组排班计划问题通常忽略第1阶段的机组配对与第2阶段的机组人员指派之间的联系。然而在现有的CCAR-121-R8的法规约束下,机组配对的结果决定着飞行机组的编制规模,进而影响飞行机组人员指派成本。为防止因飞行机组编制规模扩大带来的成本增加和不必要的资源消耗,本文提出考虑飞行机组编制规模的机组配对模型,以列生成算法为主框架,并针对定价子问题特性,设计融合状态压缩与向量支配策略的改进动态规划算法进行求解。结果表明:与传统的动态规划算法相比,子问题采用本文设计的改进动态规划算法求解,能使计算时间减少48.43%~81.65%;相比于现有的机组配对方法,本文模型生成的航班环对飞行员的平均数量需求减少3.12%,平均总成本减少5.53%。此外,本文模型通过压缩日飞行时间和日值勤期的上限,减小航班环的飞行机组编制规模,使飞行时间大于9h和值勤期大于14h的勤务数量分别减少9.10%和23.53%,部分飞行员的潜在疲劳风险得以降低。

关键词: 航空运输, 机组配对, 列生成算法, 飞行机组编制规模, 混合整数规划

Abstract: Traditional two-stage solutions to the crew scheduling problem typically neglect the connection between the first stage (crew pairing) and the second stage (crew assignment). However, under the existing CCAR-121-R8 regulations, the result of crew pairing determines the size of the flight crew, which affects the cost of crew assignment. To prevent the increased costs and unnecessary resource consumption due to the expansion of flight crew size, this paper proposes a crew pairing model that considers the size of the flight crew. Taking the column generation algorithm as the main framework, and considering the characteristics of the pricing subproblem, an improved dynamic programming algorithm incorporating state compression and vector domination strategies is designed for solving the problem. Results show that: 1) Compared with the traditional dynamic programming algorithms, using the improved dynamic programming algorithm designed in this paper to solve the subproblem reduces the computation time by 48.43%~81.65%. 2) Compared with the existing crew pairing methods, the pairing generated by the model in this paper reduces the average number of pilots required by 3.12% and the average total cost by 5.53%. In addition, the model in this paper reduces the size of the flight crew in the pairing by compressing the upper limit of daily flight time and daily duty period, which reduces the number of duties with flight time greater than 9 hours and duty period greater than 14 hours by 9.10% and 23.53% respectively, and the potential fatigue risk of some pilots is reduced.

Key words: air transportation, crew pairing, column generation algorithm, flight crew size, mixed integer programming

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