一种综合优化与可视化的建筑场地布局规划方法

IF 8 1区 工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Zhongya Mei , Qiaoting Tan , Yi Tan , Wen Yi , Siyu Luo
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引用次数: 0

摘要

施工现场布局规划(CSLP)有助于降低成本、提高生产率并降低现场和非现场施工部门的安全风险。作为一项优化挑战,它主要侧重于确定材料临时设施(TF)的最合适位置和尺寸。然而,对材料再利用的关注有限,给优化结果的实际应用带来了障碍。此外,依赖二维(2D)可视化布局展示也无法满足实际需求。为了解决这些问题,本研究提出了一种综合方法,将 CSLP 的优化和可视化结合起来,同时考虑到原生材料和再利用材料。首先,介绍了确定 TF 现场尺寸、运输频率和距离的计算方法,同时考虑了材料堆放模式和库存水平、运输过程和现场障碍物。随后,将 CSLP 问题表述为一个数学模型,旨在使总运输成本最小化。此外,还设计了一种基于贪婪算法和识别可用现场空间的启发式算法来解决该模型。通过与其他广泛使用的元启发式算法(如蚁群优化、遗传算法和粒子群优化)进行比较分析,证明了所设计的算法在解决 CSLP 问题方面的优越性。最后,还采用了基于建筑信息模型(BIM)的参数化建模,以三维格式自动、动态地展示优化结果。通过在中国重庆进行的案例研究,对所提出的方法进行了说明和验证。研究结果表明,所提出的方法可以高效、准确地生成存储和加工 TF 的三维布局,同时容纳原生材料和再利用材料。这项研究不仅丰富了现有的 CSLP 文献,还为现实世界的规划提出了切实可行的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An integrated optimization and visualization approach for construction site layout planning considering primary and reuse building materials
Construction Site Layout Planning (CSLP) facilitates cost reduction, productivity enhancement, and mitigation of safety risks across both on-site and off-site construction sectors. As an optimization challenge, it primarily focuses on determining the most suitable locations and dimensions for temporary facilities (TFs) designated for materials. However, the limited attention given to the reuse of materials poses obstacles to the practical application of optimization results. Moreover, the reliance on two-dimensional (2D) visualizations for layout presentation falls short of meeting practical demands. To address these issues, this study proposes an integrated approach that combines optimization and visualization for CSLP, taking into account both primary and reuse materials. Initially, the calculation methods for determining the on-site dimensions of TFs, transportation frequencies, and distances, considering material stacking patterns and inventory levels, transportation processes, and on-site obstacles are introduced. Subsequently, the CSLP problem is formulated as a mathematical model aimed at minimizing the total transportation cost. Furthermore, a heuristic algorithm, based on the greedy algorithm and identified available on-site space, is designed to solve this model. A comparative analysis with other widely-used meta-heuristic algorithms, such as ant colony optimization, genetic algorithms, and particle swarm optimization, demonstrates the superiority of the designed algorithm in solving the CSLP problem. Lastly, a Building Information Modeling (BIM)-based parametric modeling is employed to automatically and dynamically present the optimized results in a 3D format. The proposed approach is illustrated and validated through a case study conducted in Chongqing, China. The findings reveal that the proposed approach can efficiently and accurately produce 3D layouts for storage and processing TFs accommodating both primary and reused materials. Not only does this study enrich the existing literature on CSLP, but it also presents practical solutions for real-world planning.
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来源期刊
Advanced Engineering Informatics
Advanced Engineering Informatics 工程技术-工程:综合
CiteScore
12.40
自引率
18.20%
发文量
292
审稿时长
45 days
期刊介绍: Advanced Engineering Informatics is an international Journal that solicits research papers with an emphasis on 'knowledge' and 'engineering applications'. The Journal seeks original papers that report progress in applying methods of engineering informatics. These papers should have engineering relevance and help provide a scientific base for more reliable, spontaneous, and creative engineering decision-making. Additionally, papers should demonstrate the science of supporting knowledge-intensive engineering tasks and validate the generality, power, and scalability of new methods through rigorous evaluation, preferably both qualitatively and quantitatively. Abstracting and indexing for Advanced Engineering Informatics include Science Citation Index Expanded, Scopus and INSPEC.
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