| Maintenance Policy for Multi-Component System with Fuzzy Lifetimes |
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| 引用本文： | 赵瑞清,高金伍. Maintenance Policy for Multi-Component System with Fuzzy Lifetimes[J]. 清华大学学报, 2003, 8(1): 49-54 |
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| 作者姓名： | 赵瑞清 高金伍 |
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| 作者单位： | UncertainSystemsLaboratory,DepartmentofMathematicalSciences,StateKeyLaboratoryofIntelligentTechnologyandSystems,TsinghuaUniversity,Beijing100084,China |
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| 基金项目： | Supported by the National Natural Science Foundationof China( No. 6 980 40 0 6 ) and the Sino- French JointL aboratory for Research in Com puter Science,Controland Applied Mathem atics ( L IAMA) |
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| 摘 要： | The application of possibility theory to maintenance policies is proposed in this paper. The lifetime of a component is modeled as a fuzzy variable. Two types of replacement policies-block replacement and age replacement with fuzzy lifetimes are investigated. The theorems show that the long-run average fuzzy reward per unit time in both policies is just the expected cost per unit of time. In order to solve the proposed models,a hybrid intelligent algorithm is employed. Finally, numerical examples are provided for the sake of illustration.
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| 关 键 词： | 维修策略 多成分系统 模糊周期 遗传算法 模糊模拟 最优化问题 |
Maintenance Policy for Multi-Component System with Fuzzy Lifetimes |
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| ZHAO Ruiqing ,GAO Jinwu )Uncertain Systems Laboratory. Maintenance Policy for Multi-Component System with Fuzzy Lifetimes[J]. Tsinghua Science and Technology, 2003, 8(1): 49-54 |
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| Authors: | ZHAO Ruiqing GAO Jinwu )Uncertain Systems Laboratory |
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| Affiliation: | ZHAO Ruiqing **,GAO Jinwu )Uncertain Systems Laboratory,Department of Mathematical Sciences,State Key Laboratory of Intelligent Technology and Systems,Tsinghua University,Beijing 100084,China |
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| Abstract: | The application of possibility theory to maintenance policies is proposed in this paper. The lifetime of a component is modeled as a fuzzy variable. Two types of replacement policies-block replacement and age replacement with fuzzy lifetimes are investigated. The theorems show that the long-run average fuzzy reward per unit time in both policies is just the expected cost per unit of time. In order to solve the proposed models, a hybrid intelligent algorithm is employed. Finally, numerical examples are provided for the sake of illustration. |
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| Keywords: | maintenance policy replacement genetic algorithm fuzzy simulation |
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