Multi-objective optimization of aviation equipment maintenance resource scheduling under high-disruption conditions based on an improved NSGA-Ⅱ algorithm

Li Lan; Hui Liu; Ji-Liang Tu; Dong-Hai Li; Yang Jiao; Fu-Xiang Yuan; Li Lan; Hui Liu; Ji-Liang Tu; Dong-Hai Li; Yang Jiao; Fu-Xiang Yuan

doi:10.3934/jimo.2026128

Journal of Industrial and Management Optimization

2026, Volume 22, Issue 7: 3504-3532. doi: 10.3934/jimo.2026128

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Multi-objective optimization of aviation equipment maintenance resource scheduling under high-disruption conditions based on an improved NSGA-Ⅱ algorithm

1.
School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China
2.
College of Economics and Management, Nanchang Hangkong University, Nanchang 330063, China

Received: 08 April 2026 Revised: 15 June 2026 Accepted: 16 June 2026 Published: 26 June 2026
90B25, 90B36

Equipment maintenance-support resource scheduling under high-disruption conditions is critical to sustaining the operational readiness of essential equipment. The main challenge is coordinating maintenance-resource demand, scheduling time, and route reliability among sources of operating-environment uncertainty. To address this challenge, we developed a triangular-fuzzy-number-based multi-objective optimization model for equipment maintenance-support resource scheduling under high-disruption conditions. The model jointly minimized scheduling time, maximized route reliability, and minimized scheduling cost. To improve solution quality, an improved NSGA-Ⅱ algorithm was developed by integrating a binary-real hybrid encoding scheme, adaptive genetic operators, and a constraint-penalty mechanism. The results indicated that the proposed model and algorithm enhanced the efficiency and robustness of maintenance-resource scheduling under high-disruption conditions and revealed the coupled trade-offs among scheduling time, route reliability, and scheduling cost under multiple uncertainties. This study provides a methodological basis and practical decision support for real-time aviation equipment maintenance scheduling in complex high-risk operating environments.
- equipment maintenance under high-disruption conditions,
- resource scheduling,
- triangular fuzzy number,
- multi-objective optimization,
- NSGA-Ⅱ algorithm
Citation: Li Lan, Hui Liu, Ji-Liang Tu, Dong-Hai Li, Yang Jiao, Fu-Xiang Yuan. Multi-objective optimization of aviation equipment maintenance resource scheduling under high-disruption conditions based on an improved NSGA-Ⅱ algorithm[J]. Journal of Industrial and Management Optimization, 2026, 22(7): 3504-3532. doi: 10.3934/jimo.2026128

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Abstract

Equipment maintenance-support resource scheduling under high-disruption conditions is critical to sustaining the operational readiness of essential equipment. The main challenge is coordinating maintenance-resource demand, scheduling time, and route reliability among sources of operating-environment uncertainty. To address this challenge, we developed a triangular-fuzzy-number-based multi-objective optimization model for equipment maintenance-support resource scheduling under high-disruption conditions. The model jointly minimized scheduling time, maximized route reliability, and minimized scheduling cost. To improve solution quality, an improved NSGA-Ⅱ algorithm was developed by integrating a binary-real hybrid encoding scheme, adaptive genetic operators, and a constraint-penalty mechanism. The results indicated that the proposed model and algorithm enhanced the efficiency and robustness of maintenance-resource scheduling under high-disruption conditions and revealed the coupled trade-offs among scheduling time, route reliability, and scheduling cost under multiple uncertainties. This study provides a methodological basis and practical decision support for real-time aviation equipment maintenance scheduling in complex high-risk operating environments.

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