• Title/Summary/Keyword: Uncertain Random Variable

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A Bayesian Approach to PM Model with Random Maintenance Quality

  • Jung, Ki-Mun
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.3
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    • pp.689-696
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    • 2007
  • This paper considers a Bayesian approach to determine an optimal PM policy with random maintenance quality. Thus, we assume that the quality of a PM action is a random variable following a probability distribution. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal PM policy. Finally, the numerical examples are presented for illustrative purpose.

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Some New Results on Uncertain Age Replacement Policy

  • Zhang, Chunxiao;Guo, Congrong
    • Industrial Engineering and Management Systems
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    • v.12 no.1
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    • pp.41-45
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    • 2013
  • Age replacement policy is a commonly policy in maintenance management of spare part. It means that a spare part is always replaced at failure or fixed time after its installation, whichever occurs first. An optimal age replacement policy of spare parts concerns with finding the optimal replacement time determined by minimizing the expected cost per unit time. The age of the part was generally assumed to be a random variable in the past literatures, but in many situations, there are few or even no observed data to estimate the probability distribution of part's lifetime. In order to solve this phenomenon, a new uncertain age replacement policy has been proposed recently, in which the age of the part was assumed to be an uncertain variable. This paper discusses the optimal age replacement policies by dealing with the parts' lifetimes as different distributed uncertain variables. Several results on the optimal age replacement time are provided when the lifetimes are described by the uncertain linear, zigzag and lognormal distributions.

Optimal Control of a Flexible Link Robot with Modelling Errors (모델링 오차를 갖는 유연 링크 로봇 최적 제어)

  • 한기봉;이시복
    • Journal of KSNVE
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    • v.6 no.6
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    • pp.791-800
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    • 1996
  • Linear LQG controller has been investigated to control flexible link manipulators. The performance and complexity of these depend largely on the model upon which the controller is designed. In this study, the flexible modes of the link manipulator are considered to have uncertain parameters, which can be represented by random variable and these parameters are reflected on the weighting of performance. In this method, the exact modelling for the flexible modes is not necessary. The order of the resulting controller is much lower than the one based on a full model. Through numerical study, it is shown that the performance and the stability-robustness of the proposed controller reaches reasonably the one based on the full model.

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Subjective Point Prediction Algorithm for Decision Analysis

  • Kim, Soung-Hie
    • Journal of the Korean Operations Research and Management Science Society
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    • v.8 no.1
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    • pp.31-40
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    • 1983
  • An uncertain dynamic evolving process has been a continuing challenge to decision problems. The dynamic random variable (drv) changes which characterize such a process are very important for the decision-maker in selecting a course of action in a world that is perceived as uncertain, complex, and dynamic. Using this subjective point prediction algorithm based on a modified recursive filter, the decision-maker becomes to have periodically changing plausible points with the passage of time.

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Multiperiod Mean Absolute Deviation Uncertain Portfolio Selection

  • Zhang, Peng
    • Industrial Engineering and Management Systems
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    • v.15 no.1
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    • pp.63-76
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    • 2016
  • Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

Reliability sensitivities with fuzzy random uncertainties using genetic algorithm

  • Jafaria, Parinaz;Jahani, Ehsan
    • Structural Engineering and Mechanics
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    • v.60 no.3
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    • pp.413-431
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    • 2016
  • A sensitivity analysis estimates the effect of the change in the uncertain variable parameter on the probability of the structural failure. A novel fuzzy random reliability sensitivity measure of the failure probability is proposed to consider the effect of the epistemic and aleatory uncertainties. The uncertainties of the engineering variables are modeled as fuzzy random variables. Fuzzy quantities are treated using the ${\lambda}$-cut approach. In fact, the fuzzy variables are transformed into the interval variables using the ${\lambda}$-cut approach. Genetic approach considers different possible combinations within the search domain (${\lambda}$-cut) and calculates the parameter sensitivities for each of the combinations.

System RBDO of truss structures considering interval distribution parameters

  • Zaeimi, Mohammad;Ghoddosian, Ali
    • Structural Engineering and Mechanics
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    • v.70 no.1
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    • pp.81-96
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    • 2019
  • In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.

Minimization Models of Defective Product Inventory Cost (불량품(不良品)을 고려(考慮)한 재고비용(在庫費用) 최소화(最小化) 모형(模型))

  • Kim, Jae-Ryeon;Yu, Seung-Ho
    • Journal of Korean Society for Quality Management
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    • v.16 no.2
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    • pp.92-98
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    • 1988
  • In this paper a model is developed for an inventory system in which the number of units of acceptable quality in a replenishment lot is uncertain and the demand. during the stockout period is back ordered and. also under the same condition an inventory model with experdited stockout is developed. It is assumed that the fraction of the acceptable quality in a replenishment lot is a random variable whose probability distribution is known. The optimal replenishment policy is synthesized for such a system. A numerical example is used to illustrate the theory.

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The Two Dimensional Analysis of RF Passive Device using Stochastic Finite Element Method (확률유한요소법을 이용한 초고주파 수동소자의 2차원 해석)

  • Kim, Jun-Yeon;Jeong, Cheol-Yong;Lee, Seon-Yeong;Cheon, Chang-Ryeol
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.49 no.4
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    • pp.249-257
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    • 2000
  • In this paper, we propose the use of stochastic finite element method, that is popularly employed in mechanical structure analysis, for more practical designing purpose of RF device. The proposed method is formulated based on the vector finite element method cooperated by pertubation analysis. The method utilizes sensitivity analysis algorithm with covariance matrix of the random variables that represent for uncertain physical quantities such as length or various electrical constants to compute the probabilities of the measure of performance of the structure. For this computation one need to know the variance and covariance of the random variables that might be determined by practical experiences. The presenting algorithm has been verified by analyzing several device with different be determined by practical experiences. The presenting algorithm has been verified by analysis several device with different measure of performanes. For the convenience of formulation, two dimensional analysis has been performed to apply it into waveguide with dielectric slab. In the problem the dielectric constant of the dielectric slab is considered as random variable. Another example is matched waveguide and cavity problem. In the problem, the dimension of them are assumed to be as random variables and the expectations and variances of quality factor have been computed.

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