A Review on Uncertainty Modeling for Decentralized Supply Chain Systems

Coordinating activities among multiple independent entities in decentralized supply chain (DSC) systems are essential to ensure the smooth flow of products and/or services. The coordination becomes more difficult and challenging in the presence of uncertainties, which always occur in real-world practical scenarios. This chapter presents a literature review on quantitative modeling approaches for DSC systems under uncertainties. The articles are selected based on their relevance to this field’s specific problem descriptions, modeling, and solution approaches. The analysis is divided, based on their quantitative models and solution approaches, emphasizing optimizing DSC planning under various uncertain parameters. The analyzes reveal that most studies have used game theory approaches in modeling DSC systems with uncertain parameters. In the case of solution approaches, there is an increasing trend of using metaheuristic approaches. In contrast, very few studies have considered simulation or simulation-optimization approaches to face multiple uncertainties associated with the planning process. It is also noticed that demand uncertainty is the major parameter studied in DSC systems, followed by supply, price, and lead time uncertainties. From the major findings of the articles reviewed in this chapter, this study offers some useful research directions by highlighting the research gaps in this field.