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• W2126985139 abstract "We investigate the dynamic stochastic multicriteria decision making (SMCDM) problems, in which the criterion values take the form of log-normally distributed random variables, and the argument information is collected from different periods. We propose two new geometric aggregation operators, such as the log-normal distribution weighted geometric (LNDWG) operator and the dynamic log-normal distribution weighted geometric (DLNDWG) operator, and develop a method for dynamic SMCDM with log-normally distributed random variables. This method uses the DLNDWG operator and the LNDWG operator to aggregate the log-normally distributed criterion values, utilizes the entropy model of Shannon to generate the time weight vector, and utilizes the expectation values and variances of log-normal distributions to rank the alternatives and select the best one. Finally, an example is given to illustrate the feasibility and effectiveness of this developed method." @default.
• W2126985139 created "2016-06-24" @default.
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• W2126985139 date "2013-01-01" @default.
• W2126985139 modified "2023-10-17" @default.
• W2126985139 title "A Method to Dynamic Stochastic Multicriteria Decision Making with Log-Normally Distributed Random Variables" @default.
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• W2126985139 doi "https://doi.org/10.1155/2013/202085" @default.
• W2126985139 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3804394" @default.
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