Coordination of supply chain inventory systems with private information

This dissertation considers the problems of coordinating different supply chain inventory systems with private information under deterministic settings. These systems studied are characterized by the following properties: (a) each facility in the system has self decision-making authority, (b) cost parameters of each facility are regarded as private information that no other facilities in the system have access to, and (c) partial information is shared among the facilities. Because of the above properties, the existing approaches for systems with global information may not be applicable. Thus, new approaches for coordinating supply chain inventory systems with private information are needed. This dissertation first studies two two-echelon distribution inventory systems. Heuristics for finding the replenishment policy of each facility are developed under global information environment. In turn, the heuristics are modified to solve the problems with private information. An important characteristic of the heuristics developed for the private information environment is that they provide the same solutions as their global information counterpart. Then, more complex multi-echelon serial and assembly supply chain inventory systems with private information are studied. The solution approach decomposes the problem into separate subproblems such that the private information is divided as required. Global optimality is sought with an iterative procedure in which the subproblems negotiate the material flows between facilities. At the core of the solution procedure is a node-model that represents a facility and its corresponding private information. Using the node-model as a building block, other supply chains can be formed by linking the node-models according to the product and information flows. By computational experiments, the effect of the private information on the performance of the supply chain is tested by comparing the proposed approach against existing heuristics that utilize global information. Experimental results show that the proposed approach provides comparable results as those of the existing heuristics with global information.