Economic order quantity model under fuzzy sense when demand follows innovation diffusion process having dynamic potential market size

K.K. Aggarwal, Chandra K. Jaggi and Alok Kumar

International Journal of Services and Operations Management, 2012, vol. 13, issue 3, 361-391

Abstract: The conventional inventory models are associated with different kind of uncertainties and these uncertainties make the model unrealistic. The fuzzy set theory plays a pivotal role to address this problem. In this paper, a mathematical model has been developed for obtaining the economic order quantity (EOQ) in which the demand of the product is assumed to follow an innovation diffusion process as proposed by Fourt and Woodlock (1960). The potential market size is considered to be dynamic. To make the model more realistic an attempt has been made to solve the model in the light of fuzzy set theory under the trapezoidal membership function. The total cost formula has been derived by applying the median rule of defuzzification and the graded mean integration representation approach of defuzzification. The effectiveness of this model is illustrated with a numerical example and sensitivity analysis of the optimal solution with respect to different parameters of the system is performed.

Keywords: innovation diffusion; economic order quantity; EOQ; trapezoidal membership function; fuzzy numbers; defuzzification; function principle; median rule; graded mean integration representation; dynamic market size; potential market size; coefficient of innovation; fuzzy sets; inventory modelling; mathematical modelling. (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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