Length Optimization of MEP Pipeline Integrated Modular Based on Genetic Algorithm

This study aims to optimize the length partitioning of modular MEP systems in building construction using a genetic algorithm, addressing challenges such as avoiding fittings (e.g., tees and crosses) and achieving standardized module lengths. To this end, this paper proposes an optimization method utilizing the customization of Revit 2021. The method comprehensively considers factors such as the location of pipe fittings, module length, production, transportation, and installation, achieving a more systematic partitioning of modules. The results show that the optimized partitioning scheme effectively avoids critical pipe fittings, and the optimized module lengths are comparable to those created manually. However, the optimized scheme includes more standardized segments, which is conducive to factory-standardized production. Additionally, cost analysis reveals that production and transportation costs account for a significant proportion of total costs, while lifting costs are relatively low. Furthermore, the presence of modules with non-standard lengths introduces corresponding penalty costs. This paper discusses the advantages and limitations of the proposed method and suggests future directions for further optimizing the algorithm and improving module partitioning. The novelty of this research lies in the integration of a genetic algorithm with BIM software to optimize MEP module partitioning, offering a more efficient and systematic approach to the modular construction process.

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Publication Details

Journal
Buildings
Published
2024-11-28
DOI
https://doi.org/10.3390/buildings14123826
Citations
5
Primary Topic
Wireless Sensor Networks and IoT
Type
article
Field-Weighted Citation Impact
1.64

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article

Length Optimization of MEP Pipeline Integrated Modular Based on Genetic Algorithm

Xuefeng Zhao, Xiongtao Fan, Song Chen, Yinghui Yang et al.
5 citations
Buildings
Wireless Sensor Networks and IoT
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article

Length Optimization of MEP Pipeline Integrated Modular Based on Genetic Algorithm

Xuefeng Zhao, Xiongtao Fan, Song Chen, Yinghui Yang, Huizhong Zhang, Qiantai Yang, Gangwen Yan
article en
5 citations

Abstract

This study aims to optimize the length partitioning of modular MEP systems in building construction using a genetic algorithm, addressing challenges such as avoiding fittings (e.g., tees and crosses) and achieving standardized module lengths. To this end, this paper proposes an optimization method utilizing the customization of Revit 2021. The method comprehensively considers factors such as the location of pipe fittings, module length, production, transportation, and installation, achieving a more systematic partitioning of modules. The results show that the optimized partitioning scheme effectively avoids critical pipe fittings, and the optimized module lengths are comparable to those created manually. However, the optimized scheme includes more standardized segments, which is conducive to factory-standardized production. Additionally, cost analysis reveals that production and transportation costs account for a significant proportion of total costs, while lifting costs are relatively low. Furthermore, the presence of modules with non-standard lengths introduces corresponding penalty costs. This paper discusses the advantages and limitations of the proposed method and suggests future directions for further optimizing the algorithm and improving module partitioning. The novelty of this research lies in the integration of a genetic algorithm with BIM software to optimize MEP module partitioning, offering a more efficient and systematic approach to the modular construction process.

BuildingsVol. 14(12)
Beijing University of Technology (CN), Beijing Urban Construction Design & Development Group (China) (CN), Beijing University of Civil Engineering and Architecture (CN)
Humanities and Social Science Fund of Ministry of Education of China
Openalex Percentile: Top 15%
Wireless Sensor Networks and IoT
1.64
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