A Model-based Multi-agent Framework to Enable an Agile Response to Supply Chain Disruptions

TL;DR

This paper presents a model-based multi-agent framework that enables agile, dynamic responses to supply chain disruptions, improving adaptability without prior knowledge of specific disruptions.

Contribution

It introduces a novel multi-agent framework that facilitates real-time coordination and decision-making for supply chain resilience, unlike traditional rule-based methods.

Findings

Feasibility demonstrated through simulated case studies.

Effective response to various disruption scenarios.

Trade-offs analyzed between distributed and centralized approaches.

Abstract

Due to the COVID-19 pandemic, the global supply chain is disrupted at an unprecedented scale under uncertain and unknown trends of labor shortage, high material prices, and changing travel or trade regulations. To stay competitive, enterprises desire agile and dynamic response strategies to quickly react to disruptions and recover supply-chain functions. Although both centralized and multi-agent approaches have been studied, their implementation requires prior knowledge of disruptions and agent-rule-based reasoning. In this paper, we introduce a model-based multi-agent framework that enables agent coordination and dynamic agent decision-making to respond to supply chain disruptions in an agile and effective manner. Through a small-scale simulated case study, we showcase the feasibility of the proposed approach under several disruption scenarios that affect a supply chain network differently, and analyze performance trade-offs between the proposed distributed and centralized methods.