Volume 16, Issue 2 (4-2026)
IJOCE 2026, 16(2): 245-263 |
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Rastegar Moghaddam M. AN INTEGRATED GRAPH-BASED IFC DECISION SUPPORT FRAMEWORK FOR SUSTAINABLE BUILDING COMPONENT SELECTION. IJOCE 2026; 16 (2) :245-263
URL: http://ijoce.iust.ac.ir/article-1-676-en.html
URL: http://ijoce.iust.ac.ir/article-1-676-en.html
Department of Architecture and Urban Planning, Shahid Beheshti University, Tehran, Iran
Abstract: (232 Views)
Decision-making in the selection of sustainable building components remains one of the most persistent challenges in the construction industry. Projects involve numerous conflicting objectives and highly interdependent variables, yet the rich semantic and relational data embedded in IFC-based BIM models is rarely fully exploited for advanced analytical support. Existing approaches typically suffer from fragmented workflows, inefficient data extraction, and poor integration between modelling, optimisation, and decision-making processes. This study proposes a comprehensive, integrated data-driven decision-support framework that directly addresses these limitations. The framework transforms IFC-based BIM data into a scalable graph database using Neo4j and connects it seamlessly with multi-objective optimisation, Data Envelopment Analysis (DEA), and multi-criteria decision-making (MCDM) within a single coherent pipeline. The framework was implemented and validated on a residential building case study, considering four key sustainability objectives. Results demonstrate that the graph-based representation improves data accessibility and efficient retrieval, while the integrated pipeline effectively reduces the solution space and delivers transparent, high-quality recommendations that balance technical performance with stakeholder preferences. Compared with conventional fragmented methods, the proposed framework offers a more coherent, practical, and potentially scalable solution for complex multi-criteria decision-making problems across the Architecture, Engineering, and Construction (AEC) industry.
Keywords: Building Information Modeling, Industry Foundation Classes, Graph Database, Multi-objective Optimisation, Data Envelopment Analysis, Multi-criteria Decision-making, Sustainable Building Components
Type of Study: Research |
Subject:
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Received: 2026/03/9 | Accepted: 2026/05/11 | Published: 2026/05/13
Received: 2026/03/9 | Accepted: 2026/05/11 | Published: 2026/05/13
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