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作者机构:Northwestern Polytech Univ Sch Mech Engn Dept Ind Engn Xian 710072 Peoples R China Northwestern Polytech Univ Minist Ind & Informat Technol Key Lab Ind Engn & Intelligent Mfg Xian 710072 Peoples R China Xian Univ Sci & Technol Sch Mech Engn Xian 710054 Peoples R China
出 版 物:《RELIABILITY ENGINEERING & SYSTEM SAFETY》 (可靠性工程与系统安全)
年 卷 期:2022年第222卷第0期
页 面:108406-108406页
核心收录:
学科分类:1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0837[工学-安全科学与工程]
基 金:National Natural Science Foundation of China [71771186 71631001 72101202]
主 题:Importance measure Reliability optimization model Constraint conditions Optimization algorithm
摘 要: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.