【摘要】 随着近年来极端天气和突发公共事件的频发，航空应急运输需求增长。为解决如何在运力外调的同时尽可能保障航班正常运营的问题，通过分层求解的思路研究了航空公司参与应急运输，运力外调后导致运力减少下的航班恢复问题。首先，基于航班延误时间最小、运营成本最小为恢复目标，建立了多目标的航班优化调度整数规划模型。其次，采用分层求解的思路，用二进制搜索算法对最小允许延误时间进行计算，基于上述结果为限制条件筛选符合的弧构建航班网络模型，结合Dijkstra算法实现飞机交换次数最小，再通过Gurobi求解器计算出最小运营成本的恢复方案。最后，以航空公司的飞行计划为例验证模型及算法的可行性。结果表明：与传统运力外调下的处理方案相比，本文中提出的模型及算法提高了10.3%的航班执行率，减少了航班的取消，为航班优化调度提供了一种可行的方法。更多还原

【Abstract】 In light of the escalating frequency of extreme meteorological phenomena and emergent public incidents in recent years, the demand for emergency airlift capabilities has witnessed a marked surge. In order to ensure normal flight operations during the outward dispatch of airline aircraft, a hierarchical solution approach was used to investigate the flight recovery problem faced by airlines participating in emergency transportation due to reduced capacity. It begined with the formulation of a multi-objective integer programming model prioritizes concurrent minimization of cumulative flight delay duration and operational expenditures in disrupted scheduling scenarios, followed by implementation of a bisection search algorithm to determine the minimal permissible delay threshold through constraint stratification. Subsequent development of a flight network topology via arc selection mechanisms incorporated Dijkstra’s algorithm to minimize aircraft substitution frequency, culminating in computational optimization using the Gurobi solver to derive cost-minimal recovery strategies. Finally, the feasibility of the proposed model and algorithm was validated using an airline’s actual flight plan as a case study. The results show that, compared with traditional outward dispatch solutions, the proposed approach improves the flight execution rate by 10.3%, reduces flight cancellations, and offers an effective method for flight schedule optimization.更多还原