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Mazen A. Al-Sinan, Abdulaziz A. Bubshait and Zainab Aljaroudi
Recent advancements in machine learning (ML) applications have set the stage for the development of autonomous construction project scheduling systems. This study presents a blueprint to demonstrate how construction project schedules can be generated aut...
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Eugene Levner, Vladimir Kats, Pengyu Yan and Ada Che
High-throughput screening systems are robotic cells that automatically scan and analyze thousands of biochemical samples and reagents in real time. The problem under consideration is to find an optimal cyclic schedule of robot moves that ensures maximum ...
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Raghad Almashhour, Haneen Abuzaid and Sameh El-Sayegh
The construction industry is a dynamic and ever-evolving sector, continuously adapting to societal needs. Within this context, project managers play a pivotal role in steering projects from inception to completion. This study delves into the vital dimens...
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Jianying Wei, Yuming Liu, Xiaochun Lu, Yu Feng and Yadi Wang
Tunnel construction projects are a classic type of repetitive project, and hold a crucial position in the construction industry. The linear scheduling method (LSM) has been in the spotlight in scheduling optimization for repetitive construction projects ...
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Shalaka Hire, Sayali Sandbhor and Kirti Ruikar
With developments in Industry 4.0, there is growing momentum to adopt technology-assisted tools to support existing processes. Even though most construction processes are now computerized, safety procedures have not yet fully embraced the digital revolut...
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Basma Latrech, Taoufik Hermassi, Samir Yacoubi, Adel Slatni, Fathia Jarray, Laurent Pouget and Mohamed Ali Ben Abdallah
Systematic biases in general circulation models (GCM) and regional climate models (RCM) impede their direct use in climate change impact research. Hence, the bias correction of GCM-RCMs outputs is a primary step in such studies. This study compares the p...
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Claudio Szwarcfiter, Yale T. Herer and Avraham Shtub
Industrial projects are plagued by uncertainties, often resulting in both time and cost overruns. This research introduces an innovative approach, employing Reinforcement Learning (RL), to address three distinct project management challenges within a set...
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Ze Yu, Chuxin Wang, Yuanyuan Zhao, Zhiyuan Hu and Yuanjie Tang
The linear scheduling method (LSM) for optimization in linear projects has been the focus of numerous academic studies over the years. However, research on incorporating reverse construction activities and other practical scenarios, such as flexible acti...
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Bin Li, Caijie Yang and Zhongzhen Yang
In response to the evolving challenges of the integration and combination of multiple container terminal operations under berth water depth constraints, the multi-terminal dynamic and continuous berth allocation problem emerges as a critical issue. Based...
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Thordur Vikingur Fridgeirsson, Helgi Thor Ingason, Haukur Ingi Jonasson and Helena Gunnarsdottir
The aim of this paper is to study the main areas in which artificial intelligence (AI) will impact the field of project management in relation to cost, risk and scheduling. The research model was based on a previous study of the ten project management kn...
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