Abstract:

The aircraft assignment problem is studied from a maintenance assurance perspective. In order to ensure its continuous airworthiness, civil aircraft are required to perform maintenance tasks, i.e., scheduled inspections, at specified intervals. The scheduled inspection interval is usually controlled by the number of flight cycles (FC), flight hours (FH), or flight days (FD), whichever comes first. In order to make balanced use of the inspection interval, an aircraft assignment model for a given fleet size is developed to optimize the maintenance interval utilization, and it is solved by a reinforcement learning algorithm to minimize the variance of the FC and FH uniformly discounted at the time of maintenance interval arrival.The proposed method is computationally efficient and can be used to maximize the effectiveness of a single scheduled inspection and maintenance, saving maintenance costs and increasing aircraft utilization. Experiments are conducted by using authentic Chinese airline flight data. The experimental results show that the algorithm can find stable optimal solutions in the data of 761 flight legs in 129.448 seconds, and the Gap value is only 0.122 4%.

Key words: aircraft assignment, maintenance intervals, reinforcement learning, maintenance interval utilization, flight legs