Transshipment problem with fuzzy customer demands and fuzzy inventory costs

We consider a supply chain consisting of a supplier and locations selling an innovative product. These locations could collaborate together by transshipment which is known as product transferring adopted mainly to reduce inventory costs and to improve customer service level. In this research, we are interested in the transshipment problem where the customer demands, the holding and the shortage costs are uncertain and represented by fuzzy sets. Our objectives are to propose a transshipment policy that takes into account the fuzziness of the mentioned parameters and to derive the approximate replenishment quantities. In order to achieve these objectives, we propose a transshipment decision process considering decision makers attitudes towards risks and a hybrid algorithm based on fuzzy simulation and genetic algorithm designed to determine the approximate replenishment quantities.