资源受限条件下受扰航班恢复研究
Irregular Flight Recovery Under Resource Restriction
董兵 1彭自琛1
作者信息
- 1. 中国民用航空飞行学院空中交通管理学院 广汉 618307
- 折叠
摘要
针对机场关闭导致的航空公司飞机和航线网络资源较长时间受限的问题,论文构建了一种基于列生成的航班恢复方法.通过优化飞机执行的航班串,使用航班延误,飞机交换,航班取消三种手段对航班计划进行调整,减少取消航班的班次,使航空公司损失最小.首先使用路径模型构建多机型航班网络和航班恢复模型,其次使用构建的启发式算法生成初始恢复方案,最后使用列生成方法对航空公司遭遇突发事件后的航班中断进行恢复,对降低多机型航空公司航班取消率进行了研究.实验结果表明,与人工调整相比,该方法可以将航班取消率下降5.4%,其中与被关闭机场不直接相关的航班取消数量下降66.67%,恢复成本减少17.4%.该方法在可接受的延误水平内,显著降低了航班取消率,对航空公司航班正常运行有较高价值.
Abstract
To address the prolonged resource restrictions faced by airlines in their aircraft and route networks due to airport closures,this study presents a column generation-based approach for flight recovery.By optimizing the route executed by aircraft,utilizing strategies including flight delays,aircraft swaps and flight cancellations,adjustments are made to the original flight sched-ule,aiming to minimize the number of canceled flights and mitigate losses for the airline.Initially,a path-based model is utilized to construct a multi-type aircraft routing network and a flight recovery model.Subsequently,a heuristic algorithm is employed to gener-ate an initial recovery schedule.Finally,a column generation method is applied to reschedule a large-scale flight disruption for a given airline in the event of an unexpected incident.This research also focuses on investigating the means to reduce the flight can-cellation rate for airlines with multi-type aircrafts.Experimental results demonstrate that compared to manual adjustments,this ap-proach can reduce the flight cancellation rate by 5.4%.Specifically,the number of flight cancellations unrelated to the closed airport decreases by 66.67%,while recovery costs are reduced by 17.4%.Within an acceptable level of delay,this method significantly de-creases flight cancellation rate,delivering considerable value for airlines in maintaining normal operations.
关键词
资源受限/不正常航班/航班恢复/路径模型/列生成算法Key words
resource restriction/airline disruption/flight recovery/route model/column generation algorithm引用本文复制引用
基金项目
国家自然科学基金项目(62203451)
中国民用航空飞行学院重点科研项目(ZJ2021-09)
中央高校基本科研业务费资助项目(J2023-050)
中国民用航空飞行学院大学生创新创业训练计划项目(S202310624284)
出版年
2024
国家科技期刊平台
NSTL
万方数据