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基于萤火虫算法的塔吊位置和布局智能优化。

Intelligent Optimization of Tower Crane Location and Layout Based on Firefly Algorithm.

机构信息

College of Civil Engineering, Nanjing Tech University, Nanjing 211816, China.

Urban Planning and Design Institute, China Design Group Co., Ltd., Nanjing 210014, China.

出版信息

Comput Intell Neurosci. 2022 Jun 29;2022:6810649. doi: 10.1155/2022/6810649. eCollection 2022.

DOI:10.1155/2022/6810649
PMID:35814533
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9259253/
Abstract

The existing tower crane positioning layout mainly depends on the experience of construction personnel, and the best tower crane positioning can be found through a large number of manual data calculation. This manual method is time-consuming and impractical. In view of this, aiming at the current situation that building information modeling (BIM) software can only obtain the relative coordinates of components, this article puts forward the key technology of importing computer-aided design (CAD) graphics into geographic information system (GIS) software to automatically obtain the world coordinate information. By clarifying the transfer relationship between the component material supply point, the component initial positioning point, and the tower crane optional positioning point, as well as the cooperative relationship between each positioning point and the tower crane operation, the tower crane positioning optimization model is formed, and the firefly algorithm is used to automatically calculate and generate the best positioning layout method of the tower crane on the project site. In this study, the vertical transportation and positioning of components are studied, and intelligent construction is formed by integrating information technology. It can further enrich the functions of perception, analysis, decision-making, and optimization; realize the decision-making intelligence of industrial buildings; and achieve the organic unity of engineering construction execution system and decision-making command system.

摘要

现有的塔吊定位布局主要依赖于施工人员的经验，需要通过大量的人工数据计算来找到最佳的塔吊定位。这种人工方法既耗时又不切实际。针对建筑信息模型 (BIM) 软件只能获取构件相对坐标的现状，本文提出了将计算机辅助设计 (CAD) 图形导入地理信息系统 (GIS) 软件以自动获取世界坐标信息的关键技术。通过明确构件材料供应点、构件初始定位点和塔吊可选定位点之间的传递关系，以及各定位点与塔吊作业之间的协作关系，形成塔吊定位优化模型，并采用萤火虫算法自动计算和生成施工现场塔吊的最佳定位布局方法。本研究对构件的垂直运输和定位进行了研究，通过集成信息技术形成智能施工，可以进一步丰富感知、分析、决策和优化功能；实现工业建筑的决策智能化；实现工程施工执行系统和决策指挥系统的有机统一。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/e0f15a338f8f/CIN2022-6810649.008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/4fe66e5de2c4/CIN2022-6810649.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/e0f15a338f8f/CIN2022-6810649.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/8b665217df4e/CIN2022-6810649.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/5bac77b66f4c/CIN2022-6810649.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/83032e7dbfda/CIN2022-6810649.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/73f23bff63c0/CIN2022-6810649.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/83f43333dd16/CIN2022-6810649.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/d884623ebd25/CIN2022-6810649.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/4fe66e5de2c4/CIN2022-6810649.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f7a/9259253/e0f15a338f8f/CIN2022-6810649.008.jpg

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