Data-driven lifting-centered construction site layout planning decision approach with BIM

IF 11.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Automation in Construction Pub Date : 2025-08-13 DOI:10.1016/j.autcon.2025.106467

Rongyan Li , Hung-Lin CHI , Zhiqi Hu , Du Li , Wen Yi , Ioannis Brilakis

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引用次数: 0

Abstract

Construction site layout planning (CSLP) is essential for optimizing the placement of temporary facilities (TFs), yet it inadequately integrates tower crane characteristics, causing inefficient material transportation and safety risk. Current decision-making relies on labor-intensive data extraction, complex mathematical models, and fragmented workflows incompatible with specialized software. This paper proposes an automated data-driven lifting-centered CSLP decision approach with building information modeling (BIM) and AI to enhance TF placement efficiency. The approach incorporates three stages: automated data extraction from the BIM model with users' promotion, development of data-driven lifting-based multi-objectives CSLP decision engines, and evaluation of generated TFs placement through BIM-based simulations. Validation indicates that over 92 % of AI-generated CSLP outcomes outperform traditional methods (genetic algorithm (GA)). Experiments on a real-world project demonstrate that this approach reduces processing time to 7.93 % of GA and lowers functional costs by 11.60 %. This method assists designers in expediting the CSLP decision-making process with BIM models.

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基于BIM的以数据驱动吊装为中心的施工现场布局规划决策方法

施工现场布局规划是优化临时设施布置的关键，但未能充分结合塔机特点，造成物料运输效率低下，存在安全隐患。当前的决策依赖于劳动密集型的数据提取、复杂的数学模型和与专用软件不兼容的碎片化工作流程。本文提出了一种基于建筑信息模型（BIM）和人工智能（AI）的数据驱动的以吊装为中心的CSLP决策方法，以提高TF的放置效率。该方法包含三个阶段：在用户的推动下从BIM模型中自动提取数据，开发基于数据驱动的基于提升的多目标CSLP决策引擎，以及通过基于BIM的模拟评估生成的tf放置。验证表明，超过92%的ai生成的CSLP结果优于传统方法（遗传算法（GA））。实际工程实验表明，该方法将遗传算法的处理时间缩短至7.93%，功能成本降低11.60%。这种方法可以帮助设计师利用BIM模型加快CSLP决策过程。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Automation in Construction 工程技术-工程：土木

CiteScore

19.20

自引率

16.50%

发文量

563

审稿时长

8.5 months

期刊介绍： Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities. The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.