A resilience-driven two-stage operational chain optimization model for unmanned weapon system-of-systems under limited resource environments

Zhong, Yuanfu; Li, Hongxu; Zhuang, Xuebin

doi:10.17531/ein/188198

Artykuł - szczegóły

Tytuł artykułu

A resilience-driven two-stage operational chain optimization model for unmanned weapon system-of-systems under limited resource environments

Autorzy

Zhong Yuanfu , Li Hongxu , Zhuang Xuebin

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

DOI

10.17531/ein/188198

Warianty tytułu

Języki publikacji

Abstrakty

Enhancing the battlefield resilience of unmanned weapon system-of-systems (UWSoS) through structural reconstruction requires scheduling additional physical resources. However, they are scarce in limited resource environments. To address the challenge of resource constraints, this paper focuses on improving the resilience of UWSoS by optimizing the operational chain of tasks after a disruption. First, a task-oriented resilience metric is proposed to characterize the impact of operational chain variations on UWSoS resilience. Based on this, a two-stage operational chain optimization model for UWSoS under limited resource environments is established, which considers the optimization actions of the edge node and rear command node in different resilience phases after the interruption for resilience enhancement. Finally, extensive simulation experiments validate the effectiveness and superiority of the proposed model. This work can support decision-makers in developing new task plans in disruption scenarios and serve as a transition approach to enhance UWSoS resilience.

Słowa kluczowe

unmanned weapon system-of-systems limited resource environment operational chain optimization resilience

Wydawca

Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne

Czasopismo

Eksploatacja i Niezawodność

Rocznik

2024

Tom

Vol. 26, no. 3

Strony

art. no. 188198

Opis fizyczny

Bibliogr. 44 poz., rys., tab., wykr.

Twórcy

autor

Zhong Yuanfu

zhongyf39@mail2.sysu.edu.cn

School of Systems Science and Engineering, Sun Yat-sen University, China

autor

Li Hongxu

lihx79@mail2.sysu.edu.cn

School of Systems Science and Engineering, Sun Yat-sen University, China

autor

Zhuang Xuebin

zhuangxb@mail.sysu.edu.cn

School of Systems Science and Engineering, Sun Yat-sen University, China

https://orcid.org/0000-0001-9456-3506

Bibliografia

1. J. Chen, J. Sun, G. Wang, From unmanned systems to autonomous intelligent systems, Engineering 12 (2022) 16–19. https://doi.org/10.1016/j.eng.2021.10.007
2. B. Clark, D. Patt, H. Schramm, Mosaic warfare: Exploiting artificial intelligence and autonomous systems to implement decision-centric operations, Center for Strategic and Budgetary Assessments, 2020.
3. S. Russell, S. Hauert, R. Altman, M. Veloso, Ethics of artificial intelligence, Nature 521 (7553) (2015) 415–416. https://doi.org/10.1038/521415a
4. W. Yang, H. Qin, J. Wang, Y. Deng, Summary of the development of world military unmanned systems in 2021, Journal of China Academy of Electronics and Information Technology 4 (2022) 368–373.
5. X. Wang, Q. Guo, Research on the test platform of ground unmanned equipment system combined with virtual and real, Computer Simulation 6 (39) (2022) 15–20.
6. X. Chen, N. Bose, M. Brito, F. Khan, B. Thanyamanta, T. Zou, A review of risk analysis research for the operations of autonomous underwater vehicles, Reliability Engineering & System Safety 216 (2021) 108011.
7. Q. Wang, T. Li, Y. Xu, F. Wang, B. Diao, L. Zheng, J. Huang, How to prevent malicious use of intelligent unmanned swarms?, The Innovation 4 (2) (2023). https://doi.org/10.1016/j.xinn.2023.100396
8. A. Rosiński, J. Paś, K. Białek, P. Wetoszka, Method for assessing reliability of the power supply system for electronic security systems of intelligent buildings taking into account external natural interference, Eksploatacja i Niezawodnosc-Maintenance and Reliability (2023). https://doi.org/10.17531/ein/176375
9. M. Oszczypała, J. Ziółkowski, J. Małachowski, Semi-markov approach for reliability modelling of light utility vehicles., Eksploatacja i Niezawodnosc-Maintenance and Reliability 25 (2) (2023). https://doi.org/10.17531/ein/161859
10. D. Choeum, D.-H. Choi, Vulnerability assessment of conservation voltage reduction to load redistribution attack in unbalanced active distri- bution networks, IEEE Transactions on Industrial Informatics 17 (1) (2020) 473–483. https://doi.org/10.1109/TII.2020.2980590
11. T. Wen, Y. Deng, The vulnerability of communities in complex networks: An entropy approach, Reliability Engineering & System Safety 196 (2020) , https://doi.org/10.1016/j.ress.2019.106782
12. G. Bocewicz, E. Szwarc, J. Wikarek, P. Nielsen, Z. Banaszak, A competency-driven staff assignment approach to improving employee scheduling robustness, Eksploatacja i Niezawodnosc-Maintenance and Reliability 23 (1) (2021) 117–131. https://doi.org/10.17531/ein.2021.1.13
13. J. Li, Y. Tan, K. Yang, X. Zhang, B. Ge, Structural robustness of combat networks of weapon system-of-systems based on the operation loop, International Journal of Systems Science 48 (3) (2017) 659–674. https://doi.org/10.1080/00207721.2016.1212429
14. Y. Fu, X. Zhu, A joint age-based system replacement and component reallocation maintenance policy: Optimization, analysis and resilience, Reliability Engineering & System Safety 235 (2023) , https://doi.org/10.1016/j.ress.2023.109240
15. C. S. Holling, Resilience and stability of ecological systems, Annual Review of Ecology and Systematics 4 (1) (1973) 1–23. https://doi.org/10.1146/annurev.es.04.110173.000245
16. P. Trucco, B. Petrenj, Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems, Reliability Engineering & System Safety (2023) , https://doi.org/10.1016/j.ress.2023.109200
17. H. Mahmoud, T. Kirsch, D. O’Neil, S. Anderson, The resilience of health care systems following major disruptive events: Current practice and a path forward, Reliability Engineering & System Safety (2023) , https://doi.org/10.1016/j.ress.2023.109264
18. M. H. Oboudi, M. Mohammadi, Two-stage seismic resilience enhancement of electrical distribution systems, Reliability Engineering & System Safety (2023) , https://doi.org/10.1016/j.ress.2023.109635
19. M. Taghizadeh, M. Mahsuli, H. Poorzahedy, Probabilistic framework for evaluating the seismic resilience of transportation systems during emergency medical response, Reliability Engineering & System Safety 236 (2023) , https://doi.org/10.1016/j.ress.2023.109255
20. L. Zhen, S. Lin, C. Zhou, Green port oriented resilience improvement for traffic-power coupled networks, Reliability Engineering & System Safety 225 (2022) , https://doi.org/10.1016/j.ress.2022.108569
21. L. Liu, J. Yang, A dynamic mission abort policy for the swarm executing missions and its solution method by tailored deep reinforcement learning, Reliability Engineering & System Safety 234 (2023) , https://doi.org/10.1016/j.ress.2023.109149
22. T. Liu, G. Bai, J. Tao, Y.-A. Zhang, Y. Fang, A multistate network approach for resilience analysis of UAV swarm considering information exchange capacity, Reliability Engineering & System Safety (2023) , https://doi.org/10.1016/j.ress.2023.109606
23. Q. Sun, H. Li, Y. Wang, Y. Zhang, Multi-swarm-based cooperative reconfiguration model for resilient unmanned weapon system-of-systems, Reliability Engineering & System Safety 222 (2022) , https://doi.org/10.1016/j.ress.2022.108426
24. B. Xu, G. Bai, Y. Fang, J. Tao, et al., Failure analysis of unmanned autonomous swarm considering cascading effects, Journal of Systems Engineering and Electronics 33 (3) (2022) 759–770. https://doi.org/10.23919/JSEE.2022.000069
25. K. Wei, T. Zhang, C. Zhang, Research on resilience model of UAV swarm based on complex network dynamics, Eksploatacja i Niezawodnosc-Maintenance and Reliability 25 (4) (2023). https://doi.org/10.17531/ein/173125
26. C. Zhang, T. Liu, G. Bai, J. Tao, W. Zhu, A dynamic resilience evaluation method for cross-domain swarms in confrontation, Reliability Engineering & System Safety 244 (2024) , https://doi.org/10.1016/j.ress.2023.109904
27. X. Zhou, Y. Huang, G. Bai, B. Xu, J. Tao, The resilience evaluation of unmanned autonomous swarm with informed agents under partial failure, Reliability Engineering & System Safety 244 (2024) , https://doi.org/10.1016/j.ress.2023.109920
28. H. T. Tran, M. Balchanos, J. C. Domerc¸ant, D. N. Mavris, A framework for the quantitative assessment of performance-based system resilience, Reliability Engineering & System Safety 158 (2017) 73–84. https://doi.org/10.1016/j.ress.2016.10.014
29. H. Li, Q. Sun, Y. Zhong, Z. Huang, Y. Zhang, A soft resource optimization method for improving the resilience of UAV swarms under continuous attack, Reliability Engineering & System Safety 237 (2023) , https://doi.org/10.1016/j.ress.2023.109368
30. J. Li, D. Zhao, J. Jiang, K. Yang, Y. Chen, Capability oriented equipment contribution analysis in temporal combat networks, IEEE Transac- tions on Systems, Man, and Cybernetics: Systems 51 (2) (2018) 696–704. https://doi.org/10.1109/TSMC.2018.2882782
31. L. Bukowski, S. Werbin´ska-Wojciechowska, Using fuzzy logic to support maintenance decisions according to resilience-based maintenance concept, Eksploatacja i Niezawodnosc-Maintenance and Reliability 23 (2) (2021). https://doi.org/10.17531/ein.2021.2.9
32. C. Zhang, R. Chen, S. Wang, H. Dui, Y. Zhang, Resilience efficiency importance measure for the selection of a component maintenance strategy to improve system performance recovery, Reliability Engineering & System Safety 217 (2022) , https://doi.org/10.1016/j.ress.2021.108070
33. M. Xu, M. Ouyang, L. Hong, Z. Mao, X. Xu, Resilience-driven repair sequencing decision under uncertainty for critical infrastructure systems, Reliability Engineering & System Safety 221 (2022) , https://doi.org/10.1016/j.ress.2022.108378
34. F. Qiang, H. Xingshuo, S. Bo, R. Yi, W. Zili, Y. Dezhen, H. Yaolong, F. Ronggen, Resilience optimization for multi-UAV formation recon- figuration via enhanced pigeon-inspired optimization, Chinese Journal of Aeronautics 35 (1) (2022) 110–123. https://doi.org/10.1016/j.cja.2020.10.029
35. Z. Chen, D. Hong, W. Cui, W. Xue, Y. Wang, J. Zhong, Resilience evaluation and optimal design for weapon system of systems with dynamic reconfiguration, Reliability Engineering & System Safety (2023) , https://doi.org/10.1016/j.ress.2023.109409
36. Z. Mou, F. Gao, J. Liu, Q. Wu, Resilient UAV swarm communications with graph convolutional neural network, IEEE Journal on Selected Areas in Communications 40 (1) (2021) 393–411. https://doi.org/10.1109/JSAC.2021.3126047
37. H. T. Tran, J. C. Domerc¸ant, D. N. Mavris, A network-based cost comparison of resilient and robust system-of-systems, Procedia Computer Science 95 (2016) 126–133. https://doi.org/10.1016/j.procs.2016.09.302
38. W. Zhang, S. Huang, C. Zhu, J. Liu, L. Sun, New paradigm of command and control: Edge command and control, Command Information System and Technology 12 (1) (2021) 1–7.
39. K. Zong, F. An, W. Zhao, L. Yan, H. Liu, Analysis of mission-based command of the U.S. Air force for joint operations, Modern Defence Technology 51 (3) (2023) 66–74.
40. J. R. Cares, et al., An information age combat model, Alidade, Inc., Newport, PR, USA (Produced for the Director, Net Assessment, Office of the Secretary of Defense under Contract TPD-01-C-003) (2004).
41. Y. Tan, X. Zhang, K. Yang, Research on networked description and modeling methods of armament system-of-systems, Journal of systems & Management 21 (6) (2012) 781–786.
42. J. Li, J. Jiang, K. Yang, Y. Chen, Research on functional robustness of heterogeneous combat networks, IEEE Systems Journal 13 (2) (2018) 1487–1495. https://doi.org/10.1109/JSYST.2018.2828779
43. D. Zhao, Y. Tan, J. Li, Y. Dou, L. Li, J. Liu, Research on structural robustness of weapon system-of-systems based on heterogeneous network, Systems Engineering-Theory and Practice 39 (12) (2019) 3197–3207.
44. H. T. Tran, A complex networks approach to designing resilient system-of-systems (2015).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-123210a5-0734-42c6-96f0-a930284217da