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

2025-07-25

AI Summary

To address supply chain disruptions causing delayed responses and rigid decision-making, this paper proposes a distributed multi-agent decision-making framework integrating dual perspectives: network topology properties and heterogeneous node capabilities. Methodologically, it combines supply chain network topology analysis, distributed optimization algorithms, and simulation-based modeling to enable resilience-driven agile response. The key contributions are: (i) the first systematic characterization of the trade-offs among performance, communication overhead, and computational timeliness between distributed and centralized decision paradigms; and (ii) a paradigm shift from conventional unidimensional network analysis by embedding node-specific operational capabilities—such as capacity, flexibility, and recovery speed—into topological modeling. Empirical evaluation demonstrates that the framework improves response efficiency by 32% on average and enhances robustness—measured by disturbance tolerance—by 27% under disruption scenarios, while enabling customizable, differentiated recovery strategies.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search
• Planning, Routing, and Scheduling: Model-Based Reasoning

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

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.

Problem

• Analyzes agile supply chain decision-making using network attributes
• Compares centralized vs distributed strategies for disruption mitigation
• Evaluates performance based on agent capabilities and topology

Innovation

• Distributed decision-making using multi-agent frameworks
• Analysis based on network attributes and topology
• Performance evaluation via comprehensive case study