Maintenance scheduling of a fleet of fighter aircraft through multi-objective simulation-optimization. (September 2014)

• Record Type: Journal Article
• Authors: Mattila, Ville; Virtanen, Kai
• Is Part Of: Simulation. Volume 90:Number 9(2014:Sep.)
• Page Start: 1023
• Page End: 1040
• Publication Date: 2014-09
• Subjects: Aircraft maintenance scheduling -- multi-attribute value function -- multi-objective simulation-optimization -- simulated annealing; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549714540008
• Languages: English
• ISSNs: 0037-5497

Abstract

The maintenance scheduling problem of a fleet of fighter aircraft is considered through multi-objective simulation-optimization (MOSO). In the problem, a maintenance schedule consisting of target starting times of the maintenance activities of the aircraft is determined. The objectives are to minimize average deviation between the target and actual starting times of the activities and to maximize average aircraft availability. The objectives depend on the maintenance schedule through complex interactions due to a policy in which the need for maintenance is based on the flight hours of the aircraft cumulated during flight missions. In addition, the durations of the flight missions, maintenance activities, and failure repairs are uncertain. Therefore, an MOSO approach is applied to the problem. The approach includes a discrete-event simulation model and a state-of-the art multi-objective simulated annealing algorithm for determining non-dominated schedules. Moreover, a multi-attribute value (MAV) function is used for supporting a maintenance decision-maker (DM) in selecting the preferred non-dominated schedule for implementation. The MAV function captures incomplete information on the values of the objectives as well as on the DM's preference statements regarding the weights of the objectives. The approach is implemented as an MOSO tool whereby the DM can consider the complex interactions and uncertainties of the problem which have not been addressed in the existing literature on maintenance scheduling. The approach and the tool are illustrated with a set of test problems as well as a real-life example problem.