TY - JOUR
T1 - Importance measure construction and solving algorithm oriented to the cost-constrained reliability optimization model
AU - Liu, Mingli
AU - Wang, Dan
AU - Zhao, Jiangbin
AU - Si, Shubin
N1 - Publisher Copyright:
© 2022
PY - 2022/6
Y1 - 2022/6
N2 - Importance measures are used to prioritize the system components for achieving high efficiency and economy of reliability optimization. The existing importance measures pay more attention to evaluating the impact of component performance changes on the objective function (such as system reliability, cost and so on). Still, these importance measures do not consider the influence of constraints in the system reliability optimization models during the ranking process of components, which may leave the component with the largest importance measure almost no space to improve its reliability. For the cost-constrained reliability optimization model (ROM), this paper proposes a cost-constrained ROM-based importance measure (CRIM) by comprehensively considering the objective function and constraints, and several properties of CRIM are discussed. Then, the CRIM-based genetic algorithm (CRIGA) is developed to solve the cost-constrained ROM. The numerical experiment for different scale systems is implemented to evaluate the performance of CRIGA by comparing it with other optimization algorithms. Experimental results show that CRIGA can get better solutions with faster convergence speed and better robustness. Finally, the case on the coal transportation system of the thermal power plant is introduced to illustrate the application of CRIM and CRIGA in reliability optimization.
AB - Importance measures are used to prioritize the system components for achieving high efficiency and economy of reliability optimization. The existing importance measures pay more attention to evaluating the impact of component performance changes on the objective function (such as system reliability, cost and so on). Still, these importance measures do not consider the influence of constraints in the system reliability optimization models during the ranking process of components, which may leave the component with the largest importance measure almost no space to improve its reliability. For the cost-constrained reliability optimization model (ROM), this paper proposes a cost-constrained ROM-based importance measure (CRIM) by comprehensively considering the objective function and constraints, and several properties of CRIM are discussed. Then, the CRIM-based genetic algorithm (CRIGA) is developed to solve the cost-constrained ROM. The numerical experiment for different scale systems is implemented to evaluate the performance of CRIGA by comparing it with other optimization algorithms. Experimental results show that CRIGA can get better solutions with faster convergence speed and better robustness. Finally, the case on the coal transportation system of the thermal power plant is introduced to illustrate the application of CRIM and CRIGA in reliability optimization.
KW - Constraint conditions
KW - Importance measure
KW - Optimization algorithm
KW - Reliability optimization model
UR - http://www.scopus.com/inward/record.url?scp=85125580593&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2022.108406
DO - 10.1016/j.ress.2022.108406
M3 - 文章
AN - SCOPUS:85125580593
SN - 0951-8320
VL - 222
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 108406
ER -