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What is Automated Construction Scheduling with DRL about?

This paper introduces an automated construction scheduling optimization method utilizing Deep Reinforcement Learning (DRL) with a Valid Action Sampling (VAS) mechanism to address real-world complexities in large construction projects. The proposed DRL model, enhanced by a Graph Convolutional Network for feature extraction and a reward shaping mechanism, demonstrates improved efficiency in scheduling and rescheduling, outperforming traditional methods. The findings suggest significant advancements in project

Author

zweelynn

Language

EN