Production-inventory-distribution coordination and performance optimization for integrated multi-stage supply chains - Zhao, Shitao (2016)
The objective of this dissertation is to study the production-inventory-distribution coordination and performance optimization problems for integrated multi-stage supply chains by adopting the coordination mechanism and framework, primarily the joint consideration of inventory replenishment and the Supply Chain Operations Reference (SCOR) model. The supply chains under study include raw materials, production, transportation and distribution. There are four stages in the supply chain process: the raw material warehouse, the manufacturing/production plant, the finished product warehouse and the distribution centre/retailer. To support coordination among the supply chain parties, both the joint consideration of inventory replenishment and an SCOR model are adopted as the coordination mechanism and the framework of the research. The scope of the work is to study three distinct but inseparable problems by using rigorous analytical approaches: an integrated multi-stage supply chain with constant demand, a SCOR-based analytical coordination model for an integrated supply chain with constant demand and an integrated multi-stage supply chain with time-varying demand. The fundamental goal of this research is to study the effects of minimizing the total operational cost of multi-stage supply chains by adopting different coordination mechanisms and frameworks. The first part of the study considers an integrated production-inventory-distribution planning problem that is faced by a multinational corporation (MNC) that manages a multi-stage supply chain over an infinite time horizon. Based on the supply chain management practices of this company, the joint consideration of inventory replenishment is adopted as the coordination mechanism at the tactical and operational levels. We devise an optimal integer-ratio coordination policy for inventory replenishment across its supply chain. Under the proposed optimal integer-ratio inventory coordination policy, the total operational cost of the supply chain is demonstrated to reach its global minimum after the integrality constraints are relaxed. Numerical examples are presented with a sensitivity analysis. The computational results demonstrate that the difference in the optimal total operational costs between integer and real-number solutions is not significant. In the second part of the research, both the joint consideration of inventory replenishment and an SCOR model are adopted as the coordination mechanism and the framework in an integrated supply chain with constant demand. In the existing literature, it remains a challenge to quantify the coordination effects on supply chain performance after the implementation of such models as Collaborative Planning, Forecasting, Replenishment and SCOR. An analytical coordination model for a supply chain of an MNC is presented. To improve supply chain performance, we study the coordination among the supply chain parties from the strategic to the operational levels. Supply chain management cost which is one of level 1 metrics from the SCOR model is selected to support the MNC to select and refine the SCM strategies. An optimal integer-ratio inventory coordination policy is devised to coordinate the inventory replenishment at the tactical and operational levels. By combining the SCOR model and the integer-ratio inventory coordination policy, a systematic approach is proposed. We focus on the derivation and analysis of the total operational cost of the supply chain based on cost performance metrics across three levels of the SCOR model version 10. The total operational cost is demonstrated to reach its global minimum after the integer constraint is relaxed. The findings reinforce the proposition that the adoption of an analytical coordination model based on the metrics of the SCOR model is promising in terms of its capacity to assist decision makers in improving supply chain performance. Numerical experiments are conducted to demonstrate how to compute the optimal total operational cost in practice. The computational results demonstrate that the total operational cost savings through the SCOR-based analytical coordination model are significant. By extending the results from constant and continuous demand, an integrated multi-stage supply chain with time-varying demand over a finite planning horizon is considered in the last part of the study. With the joint consideration of inventory replenishment coordination mechanism, an optimal production-inventory-distribution policy is devised to minimize the total operational cost. The model is formulated as a mixed-integer nonlinear programming optimization problem. The problem is represented as a weighted directed acyclic graph. The global minimum total operational cost is computed in polynomial time by the developed algorithm. Two numerical examples of a seasonal product and a product over its life cycle are studied to illustrate the results. A sensitivity analysis of the system parameters is conducted to help elucidate the supply chain decision making process.