Automating look-ahead schedule generation for construction using linked-data based constraint checking and reinforcement learning

Journal article (2022)

Authors

R. K. Soman Imperial College London

Miguel Molina-Solana Universidad de Granada, Imperial College London

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Scheduling Reinforcement learning Q-learning Lean construction Linked-data Look ahead schedule (LAS) Look-ahead planning Resource constrained project scheduling problem (RCPSP)

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Published Date

2022

Language

English

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Abstract

Look-ahead planning is the stage in construction planning where information from diverse sources is integrated and plans developed for the next six/eight weeks. Poor planning of construction site activities at this stage often results in cost overruns and schedule delays. This work presents a novel Look-Ahead Schedule (LAS) generation method, which uses reinforcement learning and linked-data based constraint checking within the reward, to address the issues associated with manual look-ahead planning and help construction professionals efficiently plan construction activities at this stage. Our proposal can generate conflict-free LAS significantly faster than conventional methods, demonstrating its capability as a decision support tool during look-ahead planning meetings. Therefore, this paper extends existing knowledge in the construction informatics domain by demonstrating the application of reinforcement learning to aid data-driven look-ahead planning.