Chinese Journal of Ship Research, Volume. 16, Issue 6, 45(2021)

Maintenance strategy of ship multi-state deterioration system under reinforcement learning mode

Jianda CHENG1, Yan LIU1, Tianyun LI1, and Yuntao CHU2
Author Affiliations
  • 1School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
  • 2China Ship Development and Design Center, Wuhan 430064, China
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    References(8)

    [7] MOUSTAFA M S, MAKSOUD E Y A, SADEK S. Optimal major and minimal maintenance policies for deteriorating systems[J]. Reliability Engineering & System Safety, 83, 363-368(2004).

    [9] ZHENG R, MAKIS V. Optimal condition-based maintenance with general repair and two dependent failure modes[J]. Computers & Industrial Engineering, 141, 106322(2020).

    [10] KIM M J, MAKIS V. Optimal maintenance policy for a multi-state deteriorating system with two types of failures under general repair[J]. Computers & Industrial Engineering, 57, 298-303(2009).

    [11] [11] WANG J R, HOU S M, SU Y Y, et al. Markov decision process based multiagent system applied to aeroengine maintenance policy optimization[C]2008 Fifth International Conference on Fuzzy Systems Knowledge Discovery. Jinan, China: IEEE, 2008.

    [13] ZHOU Q, SHAO X Y, JIANG P et al. An active learning variable-fidelity metamodelling approach based on ensemble of metamodels and objective-oriented sequential sampling[J]. Journal of Engineering Design, 27, 205-231(2016).

    [17] [17] SUTTON R S, BARTO A G. Reinfcement learning: an introduction[M]. 2nd ed. Cambridge, MA: MIT Press, 2018.

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    Jianda CHENG, Yan LIU, Tianyun LI, Yuntao CHU. Maintenance strategy of ship multi-state deterioration system under reinforcement learning mode[J]. Chinese Journal of Ship Research, 2021, 16(6): 45

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    Paper Information

    Category: Ship Design and Performance

    Received: Sep. 29, 2020

    Accepted: --

    Published Online: Mar. 28, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02129

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