33rd Annual Conference of the International Group for Lean Construction (IGLC 33) - Osaka and Kyoto, Japan - 2025

https://doi.org/10.24928/2025/0102

Leveraging Multi-agent System Powered by Large Language Model to Improve Transparency and Reliability in Automated Supply Chain Coordination

Xianxiang Zhao1, Wenyi Kuang2 & Yong-Woo Kim3

1Ph.D. Student, Department of Construction Management, University of Washington, Seattle, USA, [email protected], https://orcid.org/0009-0000-8378-0644 2 Researcher, Khoury College of Computer Sciences, Northeastern University, Boston, USA, [email protected], orcid.org/0000-0002-2008-5924 3 Professor, Department of Construction Management, University of Washington, Seattle, USA, [email protected], https://orcid.org/0000-0001-7020-0700
2Researcher, Khoury College of Computer Sciences, Northeastern University, Boston, USA, [email protected], orcid.org/0000-0002-2008-5924
3Professor, Department of Construction Management, University of Washington, Seattle, USA, [email protected], https://orcid.org/0000-0001-7020-0700

Abstract

Lack of transparency and information reliability in supply chain management have been persistent challenges. Based on the LangChain and LangGraph frameworks, this research proposed a Large Language Model (LLM)-based Multi-Agent System (MAS) specifically designed to enhance information reliability and transparency in construction supply chain coordination. A prototype system composed of multiple autonomous agents was designed and developed capable of working collaboratively, sharing information, and supporting decision-making. The system comprises Supplier Agents and General Contractor Agents capable of engaging in natural language interactions. These agents coordinate the supply chain by facilitating communication about material deliveries and project progress. The prototype demonstrated the potential of LLM-based MAS in improving supply chain transparency and reliability. This research not only validated the feasibility of applying large language models in automated supply chain coordination but also offered insights for the design and implementation of future systems.

Keywords

Lean construction, Supply Chain Coordination, Large Language Model, Multi Agent System.

Files


Full Text
 

Reference

Download: BibTeX | RIS Format

Reference in APA 7th edition format:

Zhao, X., Kuang, W. & Kim, Y.. (2025). Leveraging Multi-agent System Powered by Large Language Model to Improve Transparency and Reliability in Automated Supply Chain Coordination. In Seppänen, O., Koskela, L., & Murata , K. (Eds.), Proceedings of the 33rd Annual Conference of the International Group for Lean Construction (IGLC 33) (pp. 681–692). https://doi.org/10.24928/2025/0102

Shortened reference for use in IGLC papers:

Zhao, X., Kuang, W. & Kim, Y.. (2025). Leveraging Multi-agent System Powered by Large Language Model to Improve Transparency and Reliability in Automated Supply Chain Coordination. IGLC33. https://doi.org/10.24928/2025/0102

 

Founded in 1993, the IGLC is an international network of researchers from practice and academia in architecture, engineering, and construction (AEC) who feel that the practice, education, and research of the AEC industry have to be radically renewed in order to respond to the global challenges ahead.

2015 © All Rights Reserved.