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運用遺傳演算法求解可維修串並聯系統參數

A Genetic Algorithms Approach to Determining Parameters of Repairable Series-Parallel Systems

摘要


系統可用度關係著可靠度及系統建置成本,在工業系統設計領域中是一重要課題。隨著系統結構日趨複雜,當系統中有一零件發生失效時,導致系統功能無法發揮的弊害有時相當嚴重。提升系統可靠度的同時,成本也會相對增加,故決定可用度參數是一複雜的尋優問題。串並聯系統的複置配置問題,大多仰賴系統設計人員的經驗。本研究的運用最佳化技術於可維修串並聯系統之設計,輔助系統設計人員進行系統元件參數擬定之決策,亦即在既定的系統架構下,決定各組件的平均失效時間與平均修護時間的最佳策略。本研究提出-最佳化模式與方法,先列出系統可用度估算式以及系統的總成本計算式,再以單位成本之系統可用度形成目標函數並建構最佳化數學模式,使用遺傳演算法求解模式。在遺傳演算法平行搜尋與世代演化的特性下,可快速得到符合成本效益下之系統可用度最佳化參數,輔助系統設計人員制定組件之選用策略與修復策略。

並列摘要


As the system structure becomes more and more complicated, failure of system function will result in huge damage. System availability is an important subject in the design field of industrial system as it is associated with reliability and allocation cost of systems. While improving the system's reliability, the cost is also on the upswing. Thus, the parameter of availability depends upon complex optimization. Redundancy Allocation Problem (RAP) of series-parallel system is traditionally resolved via the help of experienced system designers. We utilized optimization technology to assist the designers, during design of repairable series-parallel system, in setting up system component parameters, namely, determining the most economical policy of components' mean-time-between-failure (MTBF) and mean time-to-repair (MTTR). We proposed a three-phase method. The first phase is to list the approximate expression of system availability and total cost's computation. The second phase is to use the system availability and total cost to form an objective function and thereafter a mathematical model. The third phase is to solve the RAP model by Genetic Algorithms. With the characteristics of parallel search and generation evolution for Genetic Algorithms, it is possible to obtain rapidly and cost-effectively the optimal system parameters, so that assist the system designers in preparing component options and related repair policies.

並列關鍵字

Availability MTBF MTTR Genetic Algorithms

參考文獻


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