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dc.contributor.authorNusen, P
dc.contributor.authorBoonyung, W
dc.contributor.authorNusen, S
dc.contributor.authorPanuwatwanich, K
dc.contributor.authorChamprasert, P
dc.contributor.authorKaewmoracharoen, M
dc.date.accessioned2021-06-21T06:24:49Z
dc.date.available2021-06-21T06:24:49Z
dc.date.issued2021
dc.identifier.issn2076-3417
dc.identifier.doi10.3390/app11114716
dc.identifier.urihttp://hdl.handle.net/10072/405245
dc.description.abstractRenovation is known to be a complicated type of construction project and prone to errors compared to new constructions. The need to carry out renovation work while keeping normal busi-ness activities running, coupled with strict governmental building renovation regulations, presents an important challenge affecting construction performance. Given the current availability of robust hardware and software, building information modeling (BIM) and optimization tools have become essential tools in improving construction planning, scheduling, and resource management. This study explored opportunities to develop a multi-objective genetic algorithm (MOGA) on existing BIM. The data were retrieved from a renovation project over the 2018–2020 period. Direct and indirect project costs, actual schedule, and resource usage were tracked and retrieved to create a BIM-based MOGA model. After 500 generations, optimal results were provided as a Pareto front with 70 combi-nations among total cost, time usage, and resource allocation. The BIM-MOGA can be used as an efficient tool for construction planning and scheduling using a combination of existing BIM along with MOGA into professional practices. This approach would help improve decision-making during the construction process based on the Pareto front data provided.
dc.description.peerreviewedYes
dc.languageen
dc.publisherMDPI AG
dc.relation.ispartofpagefrom4716
dc.relation.ispartofissue11
dc.relation.ispartofjournalApplied Sciences
dc.relation.ispartofvolume11
dc.subject.fieldofresearchArtificial intelligence
dc.subject.fieldofresearchCivil engineering
dc.subject.fieldofresearchcode4602
dc.subject.fieldofresearchcode4005
dc.titleConstruction planning and scheduling of a renovation project using bim-based multi-objective genetic algorithm
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationNusen, P; Boonyung, W; Nusen, S; Panuwatwanich, K; Champrasert, P; Kaewmoracharoen, M, Construction planning and scheduling of a renovation project using bim-based multi-objective genetic algorithm, Applied Sciences, 2021, 11 (11), pp. 4716
dcterms.licensehttps://creativecommons.org/licenses/by/4.0/
dc.date.updated2021-06-21T01:47:51Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorPanuwatwanich, Kriengsak


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