Share This Special Issue

Special Issue Editors

Special Issue Information

Dear Colleagues,

For decades, the construction industry has been tightly inter-mingled with building information modeling (BIM) to cope with challenging circumstances such as schedule shortages, cost overruns, and quality conformance. Although there is strong demand for applying BIM technology, relatively little attention has been focused on the construction management applications. The aim of this Special Issue is to tackle a wide spectrum of applications of BIM in the realm of construction management, including but not limited to the following:

Project management in construction;
Integrated digital delivery in construction industry;
Digital transformation in the construction industry;
Sustainable project management.

Prof. Dr. Hee Sung Cha
Dr. Shaohua Jiang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

artificial intelligence in construction
building information modeling (BIM)
digital transformation
sustainable construction

Published Papers (1 paper)

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

23 pages, 5144 KiB

Open AccessFeature PaperArticle

Building an Information Modeling-Based System for Automatically Generating the Assembly Sequence of Precast Concrete Components Using a Genetic Algorithm

by Subin Bae, Heesung Cha and Shaohua Jiang

Appl. Sci. 2024, 14(4), 1358; https://doi.org/10.3390/app14041358 - 07 Feb 2024

Viewed by 651

Abstract

Facing a significant decrease in economic working processes, Off-Site Construction (OSC) methods have been frequently adopted in response to challenges such as declining productivity and labor shortages in the construction industry. Currently, in most OSC applications, the assembly phase is traditionally managed based on the personal experience and judgment of the site managers. This approach can lead to inaccuracies or omissions, particularly when dealing with a large amount of information on large, complex construction sites. Additionally, there are limitations in exploring more efficient and productive alternatives for rapidly adapting to changing on-site conditions. Given that the assembly phase significantly affects the OSC productivity, a systematic management approach is crucial for expanding OSC methods. Some initial studies used computer algorithms to determine the optimal assembly sequences. However, these studies often focused on geometrical characteristics, such as component weight or spatial occupancy, neglecting crucial factors in actual site planning, such as the work radius and component installation status. Moreover, these studies tended to prioritize the generation of initial assembly sequences rather than providing alternatives for adapting to evolving on-site conditions. In response to these limitations, this study presents a systematic framework utilizing a Building Information Modeling (BIM)–Genetic Algorithm (GA) approach to generate Precast Concrete (PC) component installation sequences. The developed system employs Genetic Algorithms to objectively explore diverse assembly plans, emphasizing the flexibility of accommodating evolving on-site conditions. Real on-site scenarios were simulated using this framework to explore multiple assembly plan alternatives and validate their applicability. Comprehensive interviews were conducted to validate the research and confirm the system’s potential contributions, especially at just-in-time-focused PC sites. Acknowledging a broader range of variables such as equipment and manpower, this study anticipates fostering more systematic on-site management within the context of a digitized construction environment. The proposed algorithm contributes to improving both productivity and sustainability of the construction industry by optimizing the management process of the off-site construction projects. Full article

(This article belongs to the Special Issue Application of Building Information Modeling in Construction Management)

► Show Figures

Journal Menu

Journal Browser

Application of Building Information Modeling in Construction Management

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (1 paper)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI