Modelling and analysis of strategic supply chain management systems

Abstract

This thesis is a research study on modelling and analysis of strategic supply chain management systems. In a comprehensive survey of the literature on supply chain modelling and analysis, we present and discuss the results according to three issues, namely supply chain network, supply chain uncertainties, and supply chain coordination. Although there is a considerable body of literature on these three issues of supply chain management, we observe that rich opportunities for further research still exist in these issues. This thesis focuses on a portion of these potential research areas, which are incorporating logical constraints in supply chain design models, modelling supplier's uncertainty in a two-stage supply chain, and modelling the benefits of information sharing-based supply chain partnerships. Specifically, we study and examine the following problems. First, in a strategic supply chain design model, we introduce logical constraints to include the constraints related to bills of materials (BOM). Reflecting intimate material supply relationships with vendors, the bottom level of BOM can be described as a list of specified quantities of materials or components supplied by different vendors. We can express BOM as logical rules such as "if product i will be produced in at least s of the proposed plants, then at least t of the candidate vendors must be selected". This formulation of BOM constraints provides a reasonable way to capture the role of vendors in the strategic supply chain design model. We will show how BOM constraints are formulated in our proposed mixed integer programming (MIP) model to assist in the selection of vendors and how to develop the linear representation of logical constraints. Logical constraints can also be used to represent the relationships among the main entities of a supply chain such as vendors. plants, and distribution centers. We will also show how these relationships are formulated as logical constraints. Second, we study an optimal inventory policy for a two-stage supply chain, which includes a supplier and a retailer. The supplier orders from an unstable outer source, which means the supplier can't receive the placed order on time and the supplier's lead time is variable. We use the supplier's variable lead time to formulate the uncertainty from the supplier. The supplier's variable lead time is assumed to be independently and identically distributed with mean and variance. The retailer faces customer demands which form a Poisson process with intensity 弇. Each customer demand arrival brings a batch of Q units. Both of the supplier and retailer adopt periodic-review batch-ordering policies. We present a modelling framework to demonstrate the modelling and analysis of supplier's lead time variability in this two-stage supply chain. We identify the relation between inventory costs and lead time variability. Comparing the results to the model with constant lead time, we can see that this variability can cause excess inventory. We also suggest further approaches in this topic about the reduction of the deficiency of lead time variability and the possible coordination mechanisms to reduce the variability. Third, in a two-level decentralized supply chain, we present a study aimed at quantifying the benefits of information sharing-based supply chain partnerships. Based on a modelling framework, we introduce three levels of information integration for modelling the partnerships in a two-stage supply chain consisting of a single retailer and a single manufacturer, namely decentralized control, coordinated control and centralized control. We derive the optimal inventory policies for the manufacturer and the retailer under these three different information sharing scenarios. We show that increasing information sharing among the members in a decentralized supply chain will lead to Pareto improvement in the performance of the entire chain. Specifically, both of the manufacturer and the retailer can obtain benefits in terms of reductions in inventory levels and cost savings. These three problems are very typical issues in modelling and analysis of strategic supply chain management systems. For each of them, we give the illustration of the specific settings of the supply chain structure. The relative modelling frameworks are formulated for quantitative analysis on each problem. We apply some traditional operations research techniques to carry out our modelling and analysis on these issues. Some practical cases are also included for testing and validating our mathematical modelling results.