@article{CHEN2026, 
author = {Nongtian CHEN and Yucheng ZHANG and Linlin LI and Youming ZHENG},
title = {Multi-objective optimization of robustness of aircraft scheduled maintenance task scheduling duration based on improved NSGA-Ⅱ},
year = {2026},
journal = {Acta Aeronautica et Astronautica Sinica},
volume = {47},
number = {8},
keywords = {aircraft maintenance, task scheduling, multi-objective optimization, scheduled maintenance, NSGA-Ⅱ},
url = {https://www.sciopen.com/article/10.7527/S1000-6893.2025.32675},
doi = {10.7527/S1000-6893.2025.32675},
abstract = {This paper investigates the aircraft maintenance task scheduling problem, integrating labor costs and uncertainty costs into a unified optimization framework. A multi-objective optimization method of maintenance task scheduling duration robustness based on NSGA-Ⅱ-Adaptive is proposed. The proposed method employs a novel approach combining critical path weights with buffer attenuation effects to define robustness values, and enhances the crossover and mutation processes of NSGA-Ⅱ through adaptive methods. The algorithm was tested on benchmark datasets of various scales and compared with NSGA-Ⅱs, NSGA-Ⅱ-LSA, and the standard NSGA-Ⅱ. Experimental results demonstrate that the proposed algorithm outperforms the counterparts in four performance metrics: convergence speed, number of non-dominated solutions, spacing metric, and coverage metric. Further validation through a real-world aircraft maintenance case study reveals that the algorithm reduces comprehensive deviations by 63%, 77.6%, and 77.9% compared to NSGA-Ⅱs, NSGA-Ⅱ-LSA, and NSGA-Ⅱ respectively. These findings confirm the proposed optimization method's practical applicability and effectiveness in addressing real-world maintenance scheduling challenges.}
}