A heuristic maintenance scheduling framework for a military aircraft fleet under limited maintenance capacities
Qin Zhang,
Yu Liu,
Tangfan Xiahou and
Hong-Zhong Huang
Reliability Engineering and System Safety, 2023, vol. 235, issue C
Abstract:
In many military scenarios, an aircraft fleet is oftentimes required to execute a sequence of missions with finite breaks between two adjacent missions. The performance of a fleet can be significantly improved by conducting appropriate maintenance activities on damaged aircraft during each break. The maintenance scheduling of such a scenario is, however, inherently subject to the limitation of maintenance capacities, such as repairpersons and repair facilities. Each maintenance activity contains multiple maintenance jobs that must be sequentially carried out, whereas the structural dependence of the constituent parts of each aircraft produces additional constraints to the sequence of maintenance activities. In this article, a new maintenance scheduling framework for a fleet of military aircraft is formulated to maximize the expected fleet readiness. Each maintenance activity requires specific repair facilities and repairpersons, and the limited maintenance capacities have to be arranged in a holistic manner. Due to the unexpected arrival of the next mission on battlefields, the uncertainty associated with the time duration of a break is also considered. Two heuristic algorithms are put forth to resolve the resulting optimization problem efficiently. Comparative studies show that the proposed heuristics outperform other alternative algorithms and are promising to solve large-scale problems.
Keywords: Military aircraft fleet; Maintenance scheduling; Limited maintenance capacities; Iterated greedy heuristic; Horizon splitting iterated greedy heuristic (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:235:y:2023:i:c:s0951832023001540
DOI: 10.1016/j.ress.2023.109239
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