arbiter
JournalsAccount

Joint optimization of selective maintenance decision-making and maintenance personnel allocation under limited resources

Yang Jiao et al.

Journal of Industrial and Management Optimization2026https://doi.org/10.3934/jimo.2026043article
AJG 1ABDC B
Weight
0.50

Abstract

Integrating selective maintenance strategies with personnel allocation for equipment groups is essential to meet combat missions' demands and significantly boost overall combat effectiveness. Accordingly, this study aims to maximize the probability of mission completion for equipment groups by developing a joint optimization model under constrained resource conditions. An environmental coefficient is incorporated to represent the dynamic impact of varying combat environments on the degradation states of individual units. Using a nonhomogeneous Markov model, this study calculates the state transition probabilities of units throughout the mission to derive the mission completion probabilities for both the equipment group and the overall combat cycle. To solve this model, an adaptive quantum immune algorithm is applied to the case study. These findings demonstrate that the proposed model and algorithm enhance maintenance decision-making quality and clarify optimization patterns regarding resource efficiency and dynamic personnel allocation. Thus they offer both a theoretical foundation and practical guidance for battlefield maintenance support.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.3934/jimo.2026043

Or copy a formatted citation

@article{yang2026,
  title        = {{Joint optimization of selective maintenance decision-making and maintenance personnel allocation under limited resources}},
  author       = {Yang Jiao et al.},
  journal      = {Journal of Industrial and Management Optimization},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.3934/jimo.2026043},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Joint optimization of selective maintenance decision-making and maintenance personnel allocation under limited resources

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.