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An iterative approach to robust and integrated aircraft routing and crew scheduling

机译:鲁棒性和综合性飞机路线和机组调度的迭代方法

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In airline scheduling a variety of planning and operational decision problems have to be solved. We consider the problems aircraft routing and crew pairing: aircraft and crew must be allocated to flights in a schedule in a minimal cost way. Although these problems are not independent, they are usually formulated as independent mathematical optimisation models and solved sequentially. This approach might lead to a suboptimal allocation of aircraft and crew, since a solution of one of the problems may restrict the set of feasible solutions of the problem solved later. Also, when minimal cost solutions are used in operations, a short delay of one flight can cause very severe disruptions of the schedule later in the day. We generate solutions that incur small costs and are also robust to typical stochastic variability in airline operations. We solve the two original problems iteratively. Starting from a minimal cost solution, we produce a series of solutions which are increasingly robust. Using data from domestic airline schedules we evaluate the benefits of the approach as well as the trade-off between cost and robustness. We extend our approach considering the aircraft routing problem together with two crew pairing problems, one for technical crew and one for flight attendants.
机译:在航空调度中,必须解决各种计划和运营决策问题。我们考虑了飞机路线安排和机组人员配对的问题:飞机和机组人员必须按计划以最小的成本分配给航班。尽管这些问题不是独立的,但通常将它们公式化为独立的数学优化模型并顺序解决。这种方法可能会导致飞机和机组人员的分配不理想,因为对其中一个问题的解决可能会限制后来解决的问题的可行解决方案的集合。同样,当在运营中使用最低成本的解决方案时,一班机的短暂延误可能会导致当天晚些时候的行程安排严重中断。我们提供的解决方案成本低廉,并且对航空公司运营中的典型随机波动性也很可靠。我们迭代地解决了两个原始问题。从最低成本的解决方案开始,我们提供了一系列功能日益强大的解决方案。使用来自国内航空公司航班时刻表的数据,我们评估了该方法的优势以及成本与可靠性之间的权衡。考虑到飞机路线问题以及两个机组配对问题,我们扩展了方法,一个是技术机组人员,另一个是空乘人员。

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