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

Liming Xu, Stephen Mak, Maria Minaricova, Alexandra Brintrup

TL;DR

This paper presents the first practical implementation of an autonomous supply chain (ASC) using a multi-agent system (MAS) approach, bridging theoretical ASC concepts with an end-to-end software prototype. It adapts Gaia/ROADMAP-inspired methodologies to define A2SC analysis and design, decomposing the ASC into structural entities and agent interactions, and demonstrates the approach through an autonomous meat supply chain case study. The authors provide a system architecture and a toolkit for developing A2SCs, validating the feasibility of automating integrated three-flow processes (product, information, finance) in a distributed, open ecosystem. While the prototype shows promise, it acknowledges limitations in partial automation, absence of financial flows, scalability, and robustness against disruptions, outlining concrete future work toward richer decision-making, negotiation protocols, Digital Twin integration, and higher autonomy levels.

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.

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

TL;DR

This paper presents the first practical implementation of an autonomous supply chain (ASC) using a multi-agent system (MAS) approach, bridging theoretical ASC concepts with an end-to-end software prototype. It adapts Gaia/ROADMAP-inspired methodologies to define A2SC analysis and design, decomposing the ASC into structural entities and agent interactions, and demonstrates the approach through an autonomous meat supply chain case study. The authors provide a system architecture and a toolkit for developing A2SCs, validating the feasibility of automating integrated three-flow processes (product, information, finance) in a distributed, open ecosystem. While the prototype shows promise, it acknowledges limitations in partial automation, absence of financial flows, scalability, and robustness against disruptions, outlining concrete future work toward richer decision-making, negotiation protocols, Digital Twin integration, and higher autonomy levels.

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.
Paper Structure (33 sections, 14 figures)

This paper contains 33 sections, 14 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Transition to ASCs
  4. Realisation of ASCs
  5. Agent-based Autonomous Supply Chain
  6. Agents and Multi-Agent System
  7. Multi-Agent System Approach
  8. Decomposition and Organisation
  9. Acquaintance and Interaction
  10. Interaction Protocol and Communication Language
  11. Vocabulary and Knowledge Representation
  12. A2SC Analysis and Design
  13. Decomposing ASC into Agents
  14. Designing Interactions and Messages
  15. A Case Study: an Autonomous Meat Supply Chain
  16. ...and 18 more sections

Figures (14)

  • Figure 1: Methodology for the analysis and design of A2SC systems.
  • Figure 2: Illustration of a simplified meat supply chain. The middle parts of this supply chain are the focus of our prototype.
  • Figure 3: Illustration of the CMC scenario.
  • Figure 4: Flowcharts illustrating the two main processes: replenishment and wholesale. Uppercase letters denote supply chain stakeholders: 'S' for supplier, 'W' for wholesaler, 'R' for retailer, 'L' for logistics, and '3PL' for third-party logistics provider.
  • Figure 5: Agents and heir main
  • ...and 9 more figures