A BIM-Linked Mathematical Decision Model for Energy
Retrofit Prioritisation in Existing Building Portfolios
Ashraf Elhendawi1,*, Moustafa Metwally2
1School of Civil Engineering and Built Environment, University of Greater Manchester, Bolton, UK
2Graduate School of Management (GSM), Management and Science University, Shah Alam, Malaysia
Emails: ashrafnasr86a1@yahoo.com; 012024021443@gsm.msu.edu.my
Abstract
Building information modelling is increasingly applied to structure engineering information across the life
cycle of built assets, but existing buildings are often underconnected to operational
data for retrofit prioritisation. This research proposes a BIM-connected retrofit prioritisation model
that converts building-performance information into an engineering information layer for initial screening.
The method integrates BIM-aligned feature organisation, transparent machine learning,
diagnostic validation, and scenario-driven screening to flag buildings for further assessment
by engineers. The paper proposes a workflow for institutions and cities seeking to transition from disparate
disclosure records to evidence-based retrofit prioritisation without relying on the imme-diate availability of
digital twins. The results suggest that operational, geometric, and typological features can be used to generate
interpretable screening markers that help guide engineering judge-ment, benchmarking, and incremental retrofit
strategies. This research offers a replicable model that supplements, rather than substitutes for, in-depth audit and
modelling.
Keywords: Building information modelling; Engineering science; Retrofit prioritisation; Building en-ergy
performance; Interpretable machine learning; Portfolio decision support