Automating look-ahead schedule generation for construction using linked-data based constraint checking and reinforcement learning
File(s)
Accepted version
Author(s)
Soman, Ranjith K
Molina-Solana, Miguel
Type
Journal Article
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.
Date Issued
2022-02-01
Date Acceptance
2021-11-23
Citation
Automation in Construction, 2022, 134, pp.1-16
ISSN
0926-5805
Publisher
Elsevier BV
Start Page
1
End Page
16
Journal / Book Title
Automation in Construction
Volume
134
Copyright Statement
Copyright © Elsevier Ltd. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
European Commission Directorate-General for Research and Innovation
Subjects
09 Engineering
12 Built Environment and Design
Building & Construction
Publication Status
Published
Article Number
104069
Date Publish Online
2021-12-01