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Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System

Author

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  • Hongyan Dui

    (Business College, Luoyang Polytechnic, Luoyang 471000, China
    School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Huiting Xu

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Yun-An Zhang

    (Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China)

Abstract

This paper divides the execution process of the command post system into four stages: information acquisition, information processing, decision control and response execution. It combines multilayer complex networks with a phased-mission system. Most studies have only evaluated the reliability of phased-mission systems. This paper evaluates and optimizes the reliability of a phased-mission system. In order to improve the mission success rate and maximize the reliability of a command post system, this paper provides a multitasking node criticality index, and the index is used to identify the key nodes in the command post’s four-stage network Then, the hot backup system of the node is selected to determine the redundant structure of the key node. Under the constraints of the operation and maintenance costs of key nodes, with the goal of maximizing the reliability of the information processing network layer, the multitask redundancy optimization model of each stage is established. Finally, the reliability of the missions before and after redundancy optimization is compared, using the case analysis of the four-layer network to verify the effectiveness of the proposed model.

Suggested Citation

  • Hongyan Dui & Huiting Xu & Yun-An Zhang, 2022. "Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System," Mathematics, MDPI, vol. 10(22), pages 1-15, November.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4180-:d:967189
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    References listed on IDEAS

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    Cited by:

    1. Yuhan Ma & Fanping Wei & Xiaobing Ma & Qingan Qiu & Li Yang, 2024. "Adaptive Mission Abort Planning Integrating Bayesian Parameter Learning," Mathematics, MDPI, vol. 12(16), pages 1-19, August.
    2. Wang, Chaonan & Xing, Liudong & Yu, Jingui & Guan, Quanlong & Yang, Chunhui & Yu, Min, 2023. "Phase reduction for efficient reliability analysis of dynamic k-out-of-n phased mission systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Hongyan Dui & Xinyue Wang & Haohao Zhou, 2023. "Redundancy-Based Resilience Optimization of Multi-Component Systems," Mathematics, MDPI, vol. 11(14), pages 1-16, July.

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