中断情况下的航空公司恢复问题：综述
Airline recovery problem under disruptions: A review
AI总结：
本文综述了中断情况下的航空公司恢复问题，将其分为客运导向和货运导向两类，系统梳理了恢复策略、建模与求解方法，并提出了动态实时恢复、多式联运耦合等未来研究方向。
摘要：
在实践中，客运和货运航班都容易受到意外因素的影响，例如恶劣天气、机场流量控制、机组人员缺勤、意外的飞机维修以及疫情等，这些因素都可能导致航班时刻表中断。因此，管理者需要重新分配相关资源，以确保机场能够在最小成本的基础上恢复正常运营，这就是航空公司恢复问题。航空公司恢复是一个活跃的研究领域，近年来有大量相关文献发表。为了更好地总结航空公司恢复的研究进展，首先选择关键词来检索相关研究，然后使用软件从论文数量、关键词和来源等方面对现有研究进行分析。其次，将航空公司恢复问题分为两类，即面向客运的航空公司恢复问题（POARP）和面向货运的航空公司恢复问题（COARP）。在POARP中，现有研究根据恢复策略进行分类，包括通用恢复策略、巡航速度控制策略、灵活飞机维修策略、多式联运策略、以乘客为中心的恢复策略以及航班合并策略。此外，还从中断类型、恢复策略、问题类型、目标函数和求解方法等角度对POARP进行了讨论。第三，从时效性、主观性、灵活性、可转移性和可组合性等角度对POARP和COARP进行了比较。最后，得出了结论并提出了未来的研究方向。对于未来研究，建议在动态和实时恢复、将人为因素纳入建模、多式联运耦合、其他机场流程的优化、鲁棒调度与航空公司恢复的结合以及优化算法改进等方面开展更深入的研究。
英文摘要：
In practice, both passenger and cargo flights are vulnerable to unexpected factors, such as adverse weather, airport flow control, crew absence, unexpected aircraft maintenance, and pandemic, which can cause disruptions in flight schedules. Thus, managers need to reallocate relevant resources to ensure that the airport can return to normal operations on the basis of minimum cost, which is the airline recovery problem. Airline recovery is an active research area, with a lot of publications in recent years. To better summarize the progress of airline recovery, first of all, keywords are chosen to search the relevant studies, then software is used to analyze the existing studies in terms of the number of papers, keywords, and sources. Secondly, the airline recovery problem is divided into two categories, namely Passenger-Oriented Airline Recovery Problem (POARP) and Cargo-Oriented Airline Recovery Problem (COARP). In POARP, the existing studies are classified according to recovery strategies, including common recovery strategies, cruise speed control strategy, flexible aircraft maintenance strategy, multi-modal transportation strategy, passenger-centric recovery strategy, and clubbing of flights strategy. Moreover, the POARP is discussed from the perspectives of disruption types, recovery strategies, problem types, objective functions, and solution methods. Thirdly, POARP and COARP are compared from the perspectives of timeliness, subjectivity, flexibility, transferability, and combinability. Finally, the conclusions are drawn and future study directions are provided. For future studies, it is recommended to conduct more in-depth research on dynamic and real-time recovery, incorporating human factors into the modeling, multi-modal transportation coupling, optimization of other airport processes, combination of robust scheduling and airline recovery, and optimization algorithm improvement.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
