On Implementing Autonomous Supply Chains: a Multi-Agent System Approach

TL;DR

This paper presents a novel multi-agent system methodology for implementing autonomous supply chains, demonstrated through a case study of an autonomous meat supply chain, highlighting practical design and system architecture.

Contribution

It introduces a new methodology and toolkit for designing autonomous supply chains using multi-agent systems, filling a research gap in implementation studies.

Findings

Successful implementation of an autonomous meat supply chain case study

Development of a system architecture for autonomous supply chains

Demonstration of the feasibility of multi-agent approaches in ASC

Abstract

Trade restrictions, the COVID-19 pandemic, and geopolitical conflicts have significantly exposed vulnerabilities within traditional global supply chains. These events underscore the need for organisations to establish more resilient and flexible supply chains. To address these challenges, the concept of the autonomous supply chain (ASC), characterised by predictive and self-decision-making capabilities, has recently emerged as a promising solution. However, research on ASCs is relatively limited, with no existing studies specifically focusing on their implementations. This paper aims to address this gap by presenting an implementation of ASC using a multi-agent approach. It presents a methodology for the analysis and design of such an agent-based ASC system (A2SC). This paper provides a concrete case study, the autonomous meat supply chain, which showcases the practical implementation of the A2SC system using the proposed methodology. Additionally, a system architecture and a toolkit for developing such A2SC systems are presented. Despite limitations, this work demonstrates a promising approach for implementing an effective ASC system.