Modeling And Analyzing The Dynamics Of Supply Chain Inventory System

As the competition of market is becoming increasingly intensified, the profits of companies are reduced substantially, and firms should response to customer demand in a timely way. It is significant to adjust the management policies dynamically in the face of unexpected changes. In such a situation, companies should not merely focus on short-term benefits. Instead, they should pay attention to the long-term development. Nevertheless, a lot of factors, such as complicated uncertain demand, complicated supply relationship, and complicated manufacturing process, bring challenges for the operation and management of supply chain systems. Thus, we believe that it will be of great importance for reducing costs and improving customer service by exploring the dynamics of supply chain systems.Control theories provide the advantages and opportunities to study the dynamics because there include a lot of feedback loops, delays, and nonlinearities in supply chain systems. To this end, this thesis aims at investigating the dynamics of supply chain systems with diversified structures by considering a lot of complex factors. The contributions are listed as follows:This thesis extends the stability results of the discrete time APIOBPCS model, a well-established production control model, from small lead times to arbitrary lead times. The sufficient and necessary stability conditions for odd lead times and even lead times are derived. To simplify the selection of replenishment parameters, we also provide the stability condition independent of the production lead time. It reveals that it is crucial to take into account the work-in-progress inventory when we are placing replenishment orders. The stability results provide us a basis for studying the bullwhip effect by developing a state space model. It enables us to study the bullwhip effect for unknown demand. The influences of replenishment parameters, lead times, and demand forecasting on the robustness of bullwhip effect are well analyzed.The fluctuation ranges of the inventory in the VMI supply chain system are studied via distinguishing the characteristics of VMI supply chain system and traditional supply chain systems. It is shown that the retailer's inventory fluctuation ranges are determined by the shipment lead time, dispatching policies, as well as the demand models. Furthermore, we study the features of the dynamics of the entire VMI supply chain system. It shows that the manufacturer, the vendor in the VMI system, can smooth the production process even if he chooses a rather low replenishment frequency for the retailer, in order to reduce transportation costs. To further improve system performance, we also study the impact of all sorts of parameters on the bullwhip effect for unknown demand. The research on the dynamics VMI supply chain system contribute to the literature by providing some analytical results, which can be used to provide suggestions on the implementation of VMI program.The demand is treated as exogenous variables in the existing literature on supply chain dynamics. However, the retailers can take some actions to increase customer demand. For example, displaying inventories is recognized having the motivation effect of demand. To figure out the influence of stock-dependent demand on the dynamics of supply chain system, this thesis studies the stability and nonlinear dynamics by building a switched linear model. It is shown that stock-dependent demand can not only destabilizing a supply chain system but also make the nonlinear dynamics more complicated. The results obtained help us understand the complexities of supply chain systems and also provide some guidelines on designing inventory rules.The supply relationship and operation mechanism of each firm make the investigation of the dynamics of supply network rather challenging and difficult. This thesis develops a state space model for a supply network composed of multiple retailers and multiple distributors by incorporating the topology and demand collaboration into the dynamical model. It facilitate us to design effective inventory rules based the robust control theory with the aim to reduce inventory and order fluctuations simultaneously. Numerical experiments are conducted to examine the effect of demand collaboration and network structures on the dynamics and robustness. It reveals that complex supply relationship might contribute to the mitigation of bullwhip effect.