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RISS 인기검색어
- 검색키워드
- 저자 : Rassoul Noorossana (검색결과 3 건)
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Improving Sampling Using Fuzzy LHS in Healthcare Supply Chain
Saman Siadati,Mohammad Jafar Tarokh,Rassoul Noorossana 대한산업공학회 2018 Industrial Engineeering & Management Systems Vol.17 No.2
Considering the effects of risk on supply chain in healthcare industry, we must provide a mathematical model based on the risk to re-design the supply chain network, which is a part of the optimization module, random sampling meth-ods use. One of the objectives for applying sampling methods is to determine the best method (by reducing the vari-ance and computational time) for different sizes. The large number of random parameters of the objective function value led to very high variance that required using methods for reducing the variance. In this research, our approach to handle risk analysis problems in mean approximation is using traditional sampling method namely Latin hypercube sampling. However, to reduce error in correlations between variables, it is proposed to perform a fuzzy method on the intervals to eliminate uncertainty in statistical values. Limitations in hypercube sampling will be discussed and numerical results involving a FLHS are presented and compared with Monte Carlo, simple LHS and other types of LHS. We show that the proposed method can affect the precision of mean and variance values.
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Fuzzy Risk Analysis Using Fuzzy Sampling Method
Saman Siadati,Mohammad Jafar Tarokh,Rassoul Noorossana 대한산업공학회 2017 Industrial Engineeering & Management Systems Vol.16 No.4
First step of reconfigurable supply chain network developing is understanding of risk affects. Categorizing of risk module and results of risk events considered with gathering and analyzing of data from network design parameters. These obtained data have probability distribution that shows uncertainty in parameters. In the literatures supply chain risk categorized based on occurrences rate or frequency and period or duration time and also place of occurrence. Deal with uncertainty and complexity of risk, our proposed fuzzy method can solve these problems in two aspects. Also described a fuzzy based sampling method (FLHS) that developed and used in this paper can improve our results even more than previous works. This paper suggests a novel modelling and simulation method of fuzzy sampling and fuzzy analysis system to address the dynamic risks effects in the especially the consideration of uncertainty risk event system behavior in different operational conditions.
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Siadati, Saman,Tarokh, Mohammad Jafar,Noorossana, Rassoul Korean Institute of Industrial Engineers 2017 Industrial Engineeering & Management Systems Vol.16 No.4
First step of reconfigurable supply chain network developing is understanding of risk affects. Categorizing of risk module and results of risk events considered with gathering and analyzing of data from network design parameters. These obtained data have probability distribution that shows uncertainty in parameters. In the literatures supply chain risk categorized based on occurrences rate or frequency and period or duration time and also place of occurrence. Deal with uncertainty and complexity of risk, our proposed fuzzy method can solve these problems in two aspects. Also described a fuzzy based sampling method (FLHS) that developed and used in this paper can improve our results even more than previous works. This paper suggests a novel modelling and simulation method of fuzzy sampling and fuzzy analysis system to address the dynamic risks effects in the especially the consideration of uncertainty risk event system behavior in different operational conditions.
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