Single-Period Inventory Models with Discrete Demand Under Fuzzy Environment

This paper analysis single-period inventory models with discrete demand under fuzzy environment. In the proposed models three different cases are examined. In the first case, demand is represented by a triangular fuzzy number and a discrete membership function. In the second case, demand is a stochastic variable while inventory costs such as unit holding cost and unit shortage cost are imprecise and represented by fuzzy numbers. In the third case, both demand and inventory costs are imprecise. The objective of the models is to find the product's best order quantity that minimizes the expected total cost. The expected total cost that includes fuzzy parameters is minimized by marginal analysis and defuzzified by the centroid defuzzification method. Models are experimented with illustrative examples and supported by sensitivity analyses.