Transshipment problem with uncertain customer demands and transfer lead time

This paper deals with the transshipment problem characterized by the uncertainty relative to customer demands and transfer lead time. We consider a distribution network of one supplier and N locations selling an innovative product. The customer demands and the transfer lead time are evaluated based on expert judgments and they are consequently represented by fuzzy sets. Our aims in this work are: (1) to identify a transshipment policy that takes into account the fuzziness of customer demands and transfer lead times and (2) to determine the approximate replenishment quantities which minimize the total inventory cost. In order to achieve these aims, we propose a new transshipment policy where the transshipment decision is made within the period and the possible transshipment decision moments belong to a fuzzy set. We consider the decision maker behavior types (pessimistic and optimistic) to determine the precise transshipment decision moment and the transshipment quantity. We propose a hybrid algorithm based on fuzzy simulation and genetic algorithm to approximate the optimal replenishment quantities.