Continuous Review Policy with Fuzzy Parameters in Supply Chain

The real world is full of uncertainties and parameters such as demand cannot be determined exactly. In this case, using crisp (exact) values and statistical methods due to absence of sufficient information, seems unwise. So in this paper, an approach is presented for using fuzzy numbers in continues review policy related decision-making. In this supply chain, there are two enterprises, A and B that the A enterprise responds to fuzzy demand of customer. This enterprise orders its demand based on its inventory control policy to the B enterprise. Moreover, the B enterprise obtains its demand based on its inventory control policy from a supplier with an infinite capacity. Both of these enterprises have a warehouse with limited capacity for inventory position. Also storages in two enterprises are backorder.
The most important fuzzy parameter is the customer’s demand that is given to the A enterprise. Its membership function is fuzzy trapezoidal number. Focusing on cost control and satisfying a defined and predetermined service level for both enterprises have been done in the objective function of our problem. Considering fuzzy conditions of the problem, centralization and decentralization approaches in chain are developed and after defuzzification these approaches are compared a numerical example. Then this comparison is analyzed to choose the better approach.