An EOQ inventory model with fuzzy demand multichannel distribution under effect of learning

Abstract

In this paper, we presentan ordering policies based inventory model with the effect of learning for the retail products during multichannel distribution where the demand of the product is imprecise (uncentain) in nature. The demand of the product is treated as triangular fuzzy number. As we know, the perishable items deteriorate in a short period and as soon as damage due to deterioration rate and deterioration can be ignored. Deterioration of perishable food can try to control with the help of preservation of the environment but extra charge bears to the seller or buyer. The preservation cost added in model this for more profit for the buyer. The effect of learning is holding the cost as well as ordering costand that's why the learning effect minimizes the holding cost and ordering cost.we minimized total inventory cost with respect to cycle length where demand is in imprecise in nature. The numerical example has been given for the justification of the proposed model and sensitivity analysis reflects the results of the proposed model. Few outcomes are useful when learning rate increases, retailer’s total cost decreases, and cycle length is almost fixed. In the end, the entire inventory cost keeps down with respect to cycle length. The numbers of examples describe the relevance of the present model.