基于时间区间内航线机型优化分配的机队规划方法

传统机队规划方法所形成的机队构成无法适应市场需求的波动,按照旅客需求的波动规律将航线上的时段进行分割形成时间区间,以时间区间内航线机型运行频次为决策变量,不同航线上机型的适航性限制、飞行机组的可用飞行时间、选定机型飞机的最少投放数等因素为约束条件,构造以航线机型分配的运营利润最大化为目标函数的时间区间内航线机型优化匹配模型,并结合Lagrange松弛算法求解机队规划问题.通过分析某航空公司19条航线、299个航班、6种候选机型的问题发现,该方法能够反映出航线上的机型分布特点,且形成的机队构成更能适应公司生产运营环境的变化,因此方法可行.

Airline fleet planning approach based on optimized allocation between routes and aircraft types within time intervals

Airline fleet composition formed by traditional fleet planning methods could not well adapt to the fluctuations of air demand. This paper divided time range into several time intervals for each route in the whole network by air demand fluctuation patterns. The frequencies of aircraft types flying on routes within time intervals were regarded as decision variables; Several factors including airworthiness limitations of aircraft types flying on routes, air crew available flight time and the least aircraft number of selected aircraft types in one fleet were treated as constraints; A model for optimized match between routes and aircraft types within time intervals was constructed, which considered the total operating profits of allocating appropriate aircraft types onto each route as objective function. Finally, Lagrange relaxation algorithm was used to solve airline fleet planning problem. A certain airline case including 19 routes, 299 flights and 6 candidate aircraft types indicates that this proposed approach can reflect the distributions of aircraft types on different routes. Furthermore, the formed fleet composition is more adaptability to the change of airlines' production environment compared with the previous approaches. So the model is feasible.