Supply chain optimisation, especially in partner selection, poses significant challenges for businesses. Researchers from ShanghaiTech University and Peking University have developed SCSimulator, a cutting-edge visual analytics framework that revolutionises this process. By integrating Large Language Models (LLMs) with Multi-Agent Simulation (MAS), SCSimulator enables advanced simulations, accurately reflecting complex competitive and cooperative dynamics in supply chains.
Key features of SCSimulator include visualising adaptive network structures, facilitating easy understanding of decision-making processes through Chain-of-Thought and Explainable AI techniques. This innovative framework empowers users to make informed decisions, adjust simulations iteratively, and explore various scenarios, significantly improving partner selection strategies.
The system balances agent autonomy with expert control, ensuring interpretability and flexibility. Empirical studies confirm its effectiveness in real-world applications, making SCSimulator a vital tool for enhancing supply chain resilience and decision-making. This research lays the foundation for AI-driven analytics in modern supply chain management.
For more details, visit: SCSimulator on ArXiv.
