ModulePacking: A Top-Down Generative Design Approach for Modular Key Plans
Publication: Journal of Computing in Civil Engineering
Volume 39, Issue 1
Abstract
Modular construction is increasingly recognized for its efficiency in production and assembly. Modularization, the design process that segments floor plans into discrete modular units to create a modular key plan, has been identified as being crucial for creating an economical modular construction plan. However, solving the modularization problem is often daunting, requiring extensive trial-and-error to navigate the cast array of possible configurations. To address this challenge, this study introduces ModulePacking, a top-down generative design approach aimed specifically at the modularization problem. A hierarchical design methodology is proposed, encompassing a twofold process: partition and merging, where the optimized modular key plan is merged from the partition result. A genetic algorithm is utilized to accelerate the optimization process. In the case study, ModulePacking can generate modular key plans that rival those created by human designers as well as satisfactory results for large-scale buildings where human designers might struggle. ModulePacking showcases considerable potential in assisting designers and manufacturers in optimizing the modular construction plan, ultimately contributing to the advancement of modular construction.
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Data Availability Statement
Some or all data that support the findings of this research are available from the corresponding author upon reasonable request. The Python code for the proposed algorithm is available on Gitee (2024).
Acknowledgments
This study is supported by the Collaborative Research Fund (CRF) (Project No. C7080-22GF) from the Hong Kong Research Grants Council.
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Published In
Journal of Computing in Civil Engineering
Volume 39 • Issue 1 • January 2025
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Mar 28, 2024
Accepted: Jul 9, 2024
Published online: Oct 9, 2024
Published in print: Jan 1, 2025
Discussion open until: Mar 9, 2025
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