Dynamic tail re-assignment model for optimal line-of-flight breakages

被引:0
作者
Ajyuk Jayaraj
R Sridharan
Vinay V Panicker
机构
[1] National Institute of Technology Calicut,Department of Mechanical Engineering
来源
Sādhanā | 2020年 / 45卷
关键词
Aircraft routing; line-of-flights; tail Re-assignment; multiple maintenance hubs;
D O I
暂无
中图分类号
学科分类号
摘要
The literature in aircraft routing focuses on cyclic rotation with the planned maintenance being assigned to the aircraft at the end of every rotation. The rotations are a set of flights provided with sufficient Maintenance Opportunity (MO) such that the planned maintenance could be carried out for the aircraft. In this research, a novel mathematical model has been introduced to the operational aircraft route assignment which considers both planned and ad hoc maintenances of the aircraft. A line-of-flight is defined as the set of geographic and time feasible flights being assigned to the hypothetical aircraft without any actual operational constraints. The model is formulated for the scenario where commercial planning department independently makes the line-of-flights and the maintenances have to be incorporated in those line-of-flights with minimal perturbations. In addition to the exact solution, the problem has also been solved using two heuristic solution approaches for the tailored module which is called the Tail Re-assignment, a problem dealt with by many airlines. The Tail Re-assignment problem can be considered as an optimization as well as feasibility problem. The objective of this research is to provide a quick solution that is feasible and near-optimal which can help in the managerial decisions in the tactical horizon. The model is tested with eight schedules with flights varying from 45 to 314, and additionally with multiple maintenance hubs and planning horizon of 20 days. The solution has all the hard constraints satisfied with the total number of onward flight rule breakages difference being minimal. The computation result shows that heuristic solutions solve the schedule for a medium-sized airline in quick time with less than 2% deviation from the exact solution.
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