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• W3097123504 endingPage "106892" @default.
• W3097123504 startingPage "106892" @default.
• W3097123504 abstract "In general fuzzy system, the nature of a fuzzy number is usually viewed as specific and deterministic but, in fuzzy reasoning the membership function is developed in a randomized​ sense. Here, we have studied the concept of fuzzy approximate reasoning over the modelling of a cost minimization classical economic order quantity (EOQ) inventory management problem. We have developed the model where all parameters assume randomized fuzzy set by means of fuzzy approximate reasoning. First of all, considering the probability density function of the fuzzy variable, utilizing possibility measures of fuzzy sets within we have formulated the expectations of the fuzzy membership functions then we split the model into seven several sub models accordingly. To defuzzify the fuzzy functions the traditional α -cuts and its dual k-cuts have been utilized over several feasible spaces of dual spaces of fuzzy variables. Numerical illustrations under different α -dual k cuts of the objective functions are done with the help of LINGO software via solution algorithm. Moreover, a comparative study has been done with the existing general fuzzy solution. Managerial insights are also highlighted by showing the superiority of the proposed approach. Finally, sensitivity analysis and graphical illustrations are made to justify the model. • An EOQ model with fuzzy parameters is considered. • The original model is segmented into seven sub-models based on the expectations of the fuzzy functions. • The concept of possibility theory is incorporated in the approximated fuzzy membership function. • To handle the fuzzy values, α -cuts and dual k-cuts have been utilized in dual spaces. • Graphical illustrations and sensitivity analysis are discussed." @default.
• W3097123504 created "2020-11-09" @default.
• W3097123504 creator A5078430868 @default.
• W3097123504 date "2021-02-01" @default.
• W3097123504 modified "2023-09-25" @default.
• W3097123504 title "Solving an EOQ model under fuzzy reasoning" @default.
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• W3097123504 doi "https://doi.org/10.1016/j.asoc.2020.106892" @default.
• W3097123504 hasPublicationYear "2021" @default.
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