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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
