He, C.; Liu, M.; He, W.; Wang, Z. and Hsiang, S. (2026) Addressing the information silo of construction planning constraints: A graph retrieval augmented generation approach. Engineering, Construction and Architectural Management, 33(7), pp. 5565-5591. ISSN 0969-9988
Abstract
Purpose – Removing planning constraints is crucial for ensuring a reliable construction plan and workflow. However, essential information related to these constraints is often scattered and fragmented, leading to the creation of information silos that hinder efficient decision-making. This research aims to develop a framework that integrates disjointed planning constraint attributes, thereby facilitating accurate and reliable access to constraint-related information. Design/methodology/approach – This study develops a constraint knowledge graph to organize and integrate constraint attributes with building information modeling (BIM) objects. A knowledge graph-enhanced retrieval-augmented generation (graph RAG) framework was developed to enrich large language models' (LLMs) knowledge in responding to project constraint-related queries. The framework's effectiveness was validated using a real-world building project with 1, 122 BIM objects and 37 planning constraints. Findings – Evaluation results demonstrate that the constraint knowledge graph effectively organizes and represents planning constraints information. The Graph RAG framework correctly answered all 16 testing queries, significantly outperforming traditional RAG in delivering accurate and reliable responses. A 40.6% improvement in correctness score and a 28.3% improvement in ROUGE score compared with baseline RAG were found during end-to-end performance evaluation. Originality/value – This study is the first to apply a knowledge graph for organizing construction planning constraint attributes alongside BIM objects. It innovatively utilizes a knowledge graph to enhance LLMs performance in answering constraint domain-specific queries. This research offers a practical tool for improving construction managers' awareness of planning constraints through a conversational interface. The developed framework is generalizable, allowing for expansion and representing extensive construction knowledge that facilitates knowledge-informed decision-making.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | constraint; construction planning; knowledge graph; large language model; retrieval-augmented generation |
| Index terms: | effectiveness, construction manager, construction planning, testing, methodology, workflow, project constraint, decision-making, large language model, building information modelling, performance evaluation |
| Subjects: | professional practice, information systems, profession, decision analysis, performance management, construction planning, performance measurement, management, control systems, research methods, data science |
| Topics: | Business Strategy, Engineering Principles, Risk Management, Quality Management, Site Management, Roles and Professions, Digital Applications, Research Practice, Project Management |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here