TY - JOUR
T1 - Defensive strategy optimization of consecutive-k-out-of-n systems under deterministic external risks
AU - Zhao, Jiangbin
AU - Zhang, Zaoyan
AU - Xu, Tianbo
AU - Cao, Xiangang
AU - Wang, Qiyu
AU - Cai, Zhiqiang
N1 - Publisher Copyright:
© 2022, Polish Academy of Sciences Branch Lublin. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Consecutive-k-out-of-n (Con/k/n) system, a reconfigurable system, can improve the system performance by adjusting the redundancy and assignment of components. This paper aims to determine the optimal defensive strategy of Con/k/n systems under external risks. The defensive capability of Con/k/n systems is evaluated based on real-time system reliability, and a defensive importance measure (DIM) is constructed to optimize components’ redundancy locally. To solve the proposed optimization model effectively, a DIM-based genetic algorithm (DIGA) is developed by integrating the advantages of DIM’s local search with the global search ability of the classical genetic algorithm (CGA). The numerical experiment under 36 scenarios illustrates that DIGA is more effective than CGA verified by average defensive capability, robustness, and convergence generations. Moreover, the redundancy distribution analysis of Con/k/5 systems in the optimal defensive strategy shows that the redundancy of F(G) systems is in a spaced (continuous) way under spacing k-1 risk or continuous k risk.
AB - Consecutive-k-out-of-n (Con/k/n) system, a reconfigurable system, can improve the system performance by adjusting the redundancy and assignment of components. This paper aims to determine the optimal defensive strategy of Con/k/n systems under external risks. The defensive capability of Con/k/n systems is evaluated based on real-time system reliability, and a defensive importance measure (DIM) is constructed to optimize components’ redundancy locally. To solve the proposed optimization model effectively, a DIM-based genetic algorithm (DIGA) is developed by integrating the advantages of DIM’s local search with the global search ability of the classical genetic algorithm (CGA). The numerical experiment under 36 scenarios illustrates that DIGA is more effective than CGA verified by average defensive capability, robustness, and convergence generations. Moreover, the redundancy distribution analysis of Con/k/5 systems in the optimal defensive strategy shows that the redundancy of F(G) systems is in a spaced (continuous) way under spacing k-1 risk or continuous k risk.
KW - consecutive-k-out-of-n system
KW - defensive capability
KW - external risks
KW - redundancy distribution
KW - strategy optimization
UR - http://www.scopus.com/inward/record.url?scp=85129223724&partnerID=8YFLogxK
U2 - 10.17531/ein.2022.2.12
DO - 10.17531/ein.2022.2.12
M3 - 文章
AN - SCOPUS:85129223724
SN - 1507-2711
VL - 24
SP - 306
EP - 316
JO - Eksploatacja i Niezawodnosc
JF - Eksploatacja i Niezawodnosc
IS - 2
ER -