On Implementing Autonomous Supply Chains: a Multi-Agent System Approach
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Abstract (arXiv)
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.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Oct 2023.
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Citing papers per year: 2024: 2; 2025: 4; 2026: 2.
8 papers.
- 2025Virtual Agent Economiescited by 17
- 2024Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Modelscited by 11
- 2025LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusioncited by 8
- 2025Orchestrator: Active Inference for Multi-Agent Systems in Long-Horizon Taskscited by 2
- 2025AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compressioncited by 2
- 2024What if? Causal Machine Learning in Supply Chain Risk Managementcited by 1
- 2026Reliability and Effectiveness of Autonomous AI Agents in Supply Chain Managementcited by 1
- 2026Agentic AI Autonomy Assessment: A Decision-Support Framework Towards Governed Supply Chain Systemscited by 0
- 2026Agentic AI Autonomy Assessment: A Decision-Support Framework Towards Governed Supply Chain Systems28 Jul 2026
- 2026Reliability and Effectiveness of Autonomous AI Agents in Supply Chain Management16 May 2026
- 2025AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compression15 Dec 2025
- 2025Virtual Agent Economies12 Sep 2025
- 2025Orchestrator: Active Inference for Multi-Agent Systems in Long-Horizon Tasks6 Sep 2025
- 2025LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion4 Mar 2025
- 2024What if? Causal Machine Learning in Supply Chain Risk Management24 Aug 2024
- 2024Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models5 Aug 2024