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首页> 外文期刊>Journal of Optimization in Industrial Engineering >Genetic Algorithm and Simulated Annealing for Redundancy Allocation Problem with Cold-standby Strategy
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Genetic Algorithm and Simulated Annealing for Redundancy Allocation Problem with Cold-standby Strategy

机译:遗传算法和模拟退火算法的冷备冗余分配

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This paper presents a new mathematical model for a redundancyallocation problem (RAP) withcold-standby redundancy strategy and multiple component choices.The applications of the proposed model arecommon in electrical power, transformation,telecommunication systems,etc.Manystudies have concentrated onone type of time-to-failure, butin thispaper, two components of time-to-failures which follow hypo-exponential and exponential distributionare investigated. The goal of the RAP is to select available components and redundancy level for each subsystem for maximizing system reliability under cost and weight constraints.Sincethe proposed model belongs to NP-hard class, we proposed two metaheuristic algorithms; namely, simulated annealing and genetic algorithm to solve it. In addition, a numerical example is presented to demonstrate the application of the proposed solution methodology.
机译:本文提出了一种具有冷备冗余策略和多部件选择的冗余分配问题(RAP)的新数学模型。该模型在电力,变电,电信系统等领域的应用很普遍。失效时间,但是在本文中,研究了失效时间遵循次指数分布和指数分布的两个部分。 RAP的目标是为每个子系统选择可用的组件和冗余级别,以在成本和重量约束下最大化系统可靠性。由于所提出的模型属于NP-hard类,因此我们提出了两种元启发式算法;即通过模拟退火和遗传算法求解。此外,还提供了一个数值示例来演示所提出的解决方法的应用。

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