Optimizing Building Prefabrication Strategies by Balancing Modularity and Complicatedness

Offsite construction can enhance productivity, quality, and sustainability in the building industry. However, the adoption of prefabrication strategies is limited by a lack of early-phase evaluation tools, when detailed design and cost information are unavailable. This paper proposes a decision-support multi-objective framework for developing prefabrication strategies at the conceptual design stage by balancing system modularity and complicatedness. Graph modeling is used to transform the conceptual design into modular designs under hybrid panelized-volumetric strategies. Modularity is measured using a community-based index, while complicatedness is quantified by the variance of modules’ structural complexity. Trade-off Pareto-optimal prefabrication strategies are generated using evolutionary optimization. The demonstration is implemented using an Industry Foundation Classes (IFC)-based data from an actual housing project. Results show higher modularity often increases complicatedness. The finding provides critical insights to explore prefabrication strategies in the early stages of the project development to achieve an optimal balance between the project’s modularity and complicatedness.

Authors

Institutions

Publication Details

Journal
Journal of Construction Engineering and Management
Published
2026-05-11
DOI
https://doi.org/10.1061/jcemd4.coeng-17877
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing Building Prefabrication Strategies by Balancing Modularity and Complicatedness

Hisham Said, Jianpeng Cao
Journal of Construction Engineering and Management
BIM and Construction Integration
article

Optimizing Building Prefabrication Strategies by Balancing Modularity and Complicatedness

Hisham Said, Jianpeng Cao
article en

Abstract

Offsite construction can enhance productivity, quality, and sustainability in the building industry. However, the adoption of prefabrication strategies is limited by a lack of early-phase evaluation tools, when detailed design and cost information are unavailable. This paper proposes a decision-support multi-objective framework for developing prefabrication strategies at the conceptual design stage by balancing system modularity and complicatedness. Graph modeling is used to transform the conceptual design into modular designs under hybrid panelized-volumetric strategies. Modularity is measured using a community-based index, while complicatedness is quantified by the variance of modules’ structural complexity. Trade-off Pareto-optimal prefabrication strategies are generated using evolutionary optimization. The demonstration is implemented using an Industry Foundation Classes (IFC)-based data from an actual housing project. Results show higher modularity often increases complicatedness. The finding provides critical insights to explore prefabrication strategies in the early stages of the project development to achieve an optimal balance between the project’s modularity and complicatedness.

Journal of Construction Engineering and ManagementVol. 152(7)
Santa Clara University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 8%
BIM and Construction Integration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.