不确定环境下的更换策略模型
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摘要
随着经济节奏的加快,如何提高系统运行时的可靠性和稳定性成为迫切需要研究和解决的问题.系统在使用的过程中,往往由于对可靠性问题考虑不周而使费用大大超过预算很多倍.特别是系统的突发性故障,通常会造成巨大的损失.在系统运行的过程中通过采取适当的更换策略对可能发生故障的部件做预防性更换,可以大大的降低系统的运行成本,提高系统运行的可靠性.
本文针对不确定环境下的年龄更换策略和成批更换策略,分别进行了讨论.年龄更换策略是最常用的更换策略之一,本文首先建立了模糊条件下的年龄更换模型,然后对解的性质进行分析,并给出系统部件维护最优更新周期存在且唯一的一个充分条件.为了便于应用,同时给出了一个更为直接的模糊条件下年龄更换策略最优解存在的判定条件.然后将模糊系统更新模型扩展到系统部件寿命为模糊随机变量和随机模糊变量的情况下,并建立了相应的模糊随机年龄更换模型和随机模糊年龄更换模型.
成批更换策略也是一种系统维护中常用的部件更换策略,本文将随机情况下对于成批更换策略的研究,扩展到了模糊条件下,并将部件寿命不确定性中的随机性与模糊性相结合,将所建立的模型扩展到模糊随机以及随机模糊条件下,建立了模糊随机成批更换策略模型和随机模糊更换策略模型.
为了求解所建立的模型,设计了一种新的模糊模拟方法来对模糊变量的期望值进行估计.将模糊模拟与蒙特卡洛模拟相结合,得到对模糊随机变量和随机模糊变量期望值进行估计的方法,并针对不同的情况给出了基于不确定模拟的SPSA算法、PSO算法以及混合智能算法对模型进行求解.
针对文中所建立的数学模型,分别给出了相应的数值算例.利用基于模拟的优化算法对系统单位时间运行费用的期望值及最优的维护周期进行了优化求解.结果表明了模型和算法的有效性.
As the speed up of economy, how to improve the system reliability and sta-bility become an urgent need to study and solve. The maintenance costs of system often be much higher than the budget many times, due to poor reli-ability issues. In particular the sudden failure of the system, results in huge losses, and in some cases lead to disastrous consequences. To replacement the possible failure parts can significantly reduce system operating costs and improve system reliability.
In this dissertation, both age replacement policy and block replacement policy in uncertainty evironment were discussed. The age-dependent replace-ment policy is one of the most commonly used strategy for system mainte-nance. A fuzzy age replacement model is eatablished, and a optimal renewal cycle exist theorem is also provided.
In a practical system the fuzziness and randomness are often mixed up with each other. Thus, both of the two uncertainties should be considered simultaneously. The fuzzy random age-dependent replacement policy and random fuzzy age-dependent replacement policy are also studied here, and the concept of long-run expected cost per unit time is also extended. In order to facilitate the application, at the same time gives a more direct method to determine the existence of the optimal solution.
The block replacement plocy is also a commonly used maintenace pol-icy. This paper extends the random block replacement policy to the fuzzy, fuzzy random and random fuzzy case and establishes the uncertainty block replacement models.
In order to get the best solution of the proposed model and get the optimal solution, a new fuzzy simulation algorithm to calculate the expected value of fuzzy variables is presented, and based on the simulation technique, SPSA algorithm, PSO algorithm and a new hybride algorithm is employed.
At the end of this dissertation, the numerical examples are enumerated, and solved through the proposed algorithm. The results illustrate the effec-tiveness of the models and algorithm.
本文针对不确定环境下的年龄更换策略和成批更换策略,分别进行了讨论.年龄更换策略是最常用的更换策略之一,本文首先建立了模糊条件下的年龄更换模型,然后对解的性质进行分析,并给出系统部件维护最优更新周期存在且唯一的一个充分条件.为了便于应用,同时给出了一个更为直接的模糊条件下年龄更换策略最优解存在的判定条件.然后将模糊系统更新模型扩展到系统部件寿命为模糊随机变量和随机模糊变量的情况下,并建立了相应的模糊随机年龄更换模型和随机模糊年龄更换模型.
成批更换策略也是一种系统维护中常用的部件更换策略,本文将随机情况下对于成批更换策略的研究,扩展到了模糊条件下,并将部件寿命不确定性中的随机性与模糊性相结合,将所建立的模型扩展到模糊随机以及随机模糊条件下,建立了模糊随机成批更换策略模型和随机模糊更换策略模型.
为了求解所建立的模型,设计了一种新的模糊模拟方法来对模糊变量的期望值进行估计.将模糊模拟与蒙特卡洛模拟相结合,得到对模糊随机变量和随机模糊变量期望值进行估计的方法,并针对不同的情况给出了基于不确定模拟的SPSA算法、PSO算法以及混合智能算法对模型进行求解.
针对文中所建立的数学模型,分别给出了相应的数值算例.利用基于模拟的优化算法对系统单位时间运行费用的期望值及最优的维护周期进行了优化求解.结果表明了模型和算法的有效性.
As the speed up of economy, how to improve the system reliability and sta-bility become an urgent need to study and solve. The maintenance costs of system often be much higher than the budget many times, due to poor reli-ability issues. In particular the sudden failure of the system, results in huge losses, and in some cases lead to disastrous consequences. To replacement the possible failure parts can significantly reduce system operating costs and improve system reliability.
In this dissertation, both age replacement policy and block replacement policy in uncertainty evironment were discussed. The age-dependent replace-ment policy is one of the most commonly used strategy for system mainte-nance. A fuzzy age replacement model is eatablished, and a optimal renewal cycle exist theorem is also provided.
In a practical system the fuzziness and randomness are often mixed up with each other. Thus, both of the two uncertainties should be considered simultaneously. The fuzzy random age-dependent replacement policy and random fuzzy age-dependent replacement policy are also studied here, and the concept of long-run expected cost per unit time is also extended. In order to facilitate the application, at the same time gives a more direct method to determine the existence of the optimal solution.
The block replacement plocy is also a commonly used maintenace pol-icy. This paper extends the random block replacement policy to the fuzzy, fuzzy random and random fuzzy case and establishes the uncertainty block replacement models.
In order to get the best solution of the proposed model and get the optimal solution, a new fuzzy simulation algorithm to calculate the expected value of fuzzy variables is presented, and based on the simulation technique, SPSA algorithm, PSO algorithm and a new hybride algorithm is employed.
At the end of this dissertation, the numerical examples are enumerated, and solved through the proposed algorithm. The results illustrate the effec-tiveness of the models and algorithm.
引文
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