A Distributed Approach for Agile Supply Chain Decision-Making Based on Network Attributes

In recent years, the frequent occurrence of disruptions has had a negative impact on global supply chains. To stay competitive, enterprises strive to remain agile through the implementation of efficient and effective decision-making strategies in reaction to disruptions. A significant effort has been made to develop these agile disruption mitigation approaches, leveraging both centralized and distributed decision-making strategies. Though trade-offs of centralized and distributed approaches have been analyzed in existing studies, no related work has been found on understanding supply chain performance based on the network
attributes
of the disrupted supply chain entities. In this paper, we characterize supply chains from a capability and network topological perspective and investigate the use of a distributed decision-making approach based on classical multi-agent frameworks. The performance of the distributed framework is evaluated through a comprehensive case study that investigates the performance of the supply chain as a function of the network structure and agent attributes within the network in the presence of a disruption. Comparison to a centralized decision-making approach highlights trade-offs between performance, computation time, and network communication based on the decision-making strategy and network architecture. Practitioners can use the outcomes of our studies to design response strategies based on agent capabilities, network attributes, and desired supply chain performance.
Note to Practitioners
—This research is motivated by the challenges in determining agile decision-making strategies that enable a supply chain enterprise to adapt to disruptions while taking into account the network-based attributes of the disrupted agent and the requirements of the supply chain system. Existing approaches in the literature focus on providing one feasible decision-making strategy based on specific performance metrics. This paper investigates both centralized and distributed approaches to better understand the differences between the response strategies in the case of supplier loss. More specifically, we design a supply chain instance and conduct a case study to evaluate the performance of the centralized and distributed approaches in terms of several common performance metrics used in practice. The case study provides insights for users to select a decision-making approach based on the network attributes and agent capabilities of the supply chain. The impact of network uncertainties and risk assessment are not considered in this work. Future studies will investigate a stochastic supply chain environment and heterogeneous risk management framework in the context of agile decision-making for disrupted supply chain enterprises.