Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach
Construction schedules play an important role in construction project management. However, during construction activities, risks may arise due to unexpected schedule changes, resulting in the ineffective delivery of projects. This study aims to reveal the law of schedule change risk propagation and...
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2020-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/8854609 |
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doaj-a44f13a2a5714761a4ede2041a5efda62020-12-21T11:41:27ZengHindawi-WileyComplexity1076-27871099-05262020-01-01202010.1155/2020/88546098854609Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network ApproachYusi Cheng0Jingfeng Yuan1Lei Zhu2Wei Li3School of Civil Engineering, Southeast University, Nanjing 210096, ChinaSchool of Civil Engineering, Southeast University, Nanjing 210096, ChinaSchool of Civil Engineering, Southeast University, Nanjing 210096, ChinaSchool of Civil Engineering, Southeast University, Nanjing 210096, ChinaConstruction schedules play an important role in construction project management. However, during construction activities, risks may arise due to unexpected schedule changes, resulting in the ineffective delivery of projects. This study aims to reveal the law of schedule change risk propagation and to analyze the effects on the risk propagation through numerical simulations. First, construction projects are represented by activity-on-node (AON) networks. A model of risk propagation is then built based on a susceptible-infected (SI) model considering the effects of the nodal characteristics on the propagation process. Next, the model is tested on a real-world project to examine cascading failures with varying parameters. The experimental results demonstrate that the model is effective in identifying the activities most capable of affecting a project schedule and evaluating the impact of schedule change risk propagation. This study will provide a basis for enhancing the robustness of AON networks and controlling the propagation of schedule change risks.http://dx.doi.org/10.1155/2020/8854609 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yusi Cheng Jingfeng Yuan Lei Zhu Wei Li |
spellingShingle |
Yusi Cheng Jingfeng Yuan Lei Zhu Wei Li Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach Complexity |
author_facet |
Yusi Cheng Jingfeng Yuan Lei Zhu Wei Li |
author_sort |
Yusi Cheng |
title |
Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach |
title_short |
Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach |
title_full |
Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach |
title_fullStr |
Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach |
title_full_unstemmed |
Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach |
title_sort |
risk propagation model and simulation of schedule change in construction projects: a complex network approach |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2020-01-01 |
description |
Construction schedules play an important role in construction project management. However, during construction activities, risks may arise due to unexpected schedule changes, resulting in the ineffective delivery of projects. This study aims to reveal the law of schedule change risk propagation and to analyze the effects on the risk propagation through numerical simulations. First, construction projects are represented by activity-on-node (AON) networks. A model of risk propagation is then built based on a susceptible-infected (SI) model considering the effects of the nodal characteristics on the propagation process. Next, the model is tested on a real-world project to examine cascading failures with varying parameters. The experimental results demonstrate that the model is effective in identifying the activities most capable of affecting a project schedule and evaluating the impact of schedule change risk propagation. This study will provide a basis for enhancing the robustness of AON networks and controlling the propagation of schedule change risks. |
url |
http://dx.doi.org/10.1155/2020/8854609 |
work_keys_str_mv |
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1714988513372405760 |