Emerging problems in supply chain management.

摘要

In the first part of the dissertation, we consider the problem of demand forecast sharing in supply chains. Information sharing within a supply chain improves the accuracy of demand forecasts. A more accurate demand forecast contributes to higher revenue through better pricing policy and lower inventory and shortage costs through better production scheduling, ordering and replenishment policies. The existing literature has analyzed the latter benefits of information sharing within a supply chain. We extend and complement prior research by addressing the benefits related to customer demand management (pricing) of information sharing in a supply chain.; In the second part of the dissertation, we investigate the possibility of minimizing the investment on safety stocks by redesigning the manufacturing and distribution process. The product family consisting of one product and two products are studied in detail. Conditions and insights for better supply chain management are developed. These conditions and insights enable us not only to decide when a process redesigning activity is appropriate, but also to suggest the scale and the format of the process redesign. Based on the obtained results, two procedures, namely re-sequencing and merging, are developed. Finally, we demonstrate how these procedures can be extended to the product family consisting of multiple products in a hierarchical manner.; In the third part of the dissertation, we study a two-stage supply chain under random yields in the upstream and random demands in the downstream. We build a period review inventory model that allows for linear stage dependent production and transportation costs and general (not necessarily linear) holding and shortage costs. This model explicitly accounts for proportional random yields at each stage. We provide a stochastic dynamic programming formulation to minimize the discounted expected costs. We show that optimal policy exists, and is a state dependent critical point type. We characterize the order of stages which will yield minimum supply chain costs. We further extend to the model by having the option of processing some of the work-in-process (wip), and disposing of the rest between stages. Finally we do numerical studies.