Prefabricated beam-slab structure optimization based on multi-layer graphical representation and genetic-RAO algorithm
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Article number | 103050 |
Journal / Publication | Advanced Engineering Informatics |
Volume | 64 |
Online published | 18 Dec 2024 |
Publication status | Online published - 18 Dec 2024 |
Link(s)
Abstract
The beam-slab structure optimization problem is a complex large-scale combinatorial problem. Traditionally, structural design has heavily relied on engineers’ experience using trial-and-error methods, while optimization algorithms require complex parameter tuning, which deviates from practical engineering needs. To bridge this gap, this study proposes an innovative workflow integrating a Genetic-RAO Algorithm with Building Information Modeling to enhance the structural optimization process. The proposed workflow employs a multi-layer graph data structure to model the beam-slab structures, mapping all optimization variables to the edges of the graph, thereby enabling efficient manipulation of layout, load transfers, and component properties of structural schemes. The proposed algorithm eliminates the need for complex parameter tuning, enhancing accessibility and adaptability for practical engineering applications. Computational experiments and case studies demonstrate the proposed algorithm achieves cost reductions of 8.69%, 16.14%, 12.07% and 6.42% across four floor plans compared to the conventional genetic algorithm. Additionally, automating result visualization within the Revit platform promotes subsequent design modifications and fosters multi-disciplinary collaboration. These findings indicate that the proposed workflow significantly improves cost-effectiveness and efficiency in structural engineering optimization, offering a practical solution for the industry.
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Research Area(s)
- Beam-slab structure, Structural optimization, Meta-heuristic algorithm, RAO algorithm, Building information modeling
Citation Format(s)
In: Advanced Engineering Informatics, Vol. 64, 103050, 03.2025.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review