{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T11:15:48Z","timestamp":1783163748865,"version":"3.54.6"},"reference-count":59,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T00:00:00Z","timestamp":1778198400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001839","name":"University Grants Committee","doi-asserted-by":"publisher","award":["C7080-22GF"],"award-info":[{"award-number":["C7080-22GF"]}],"id":[{"id":"10.13039\/501100001839","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.aei.2026.104799","type":"journal-article","created":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T11:33:00Z","timestamp":1778585580000},"page":"104799","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PC","title":["HyperMB: A hypergraph representation and learning framework for modular building layout design decisions"],"prefix":"10.1016","volume":"74","author":[{"given":"Yuchen","family":"Gao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4674-0357","authenticated-orcid":false,"given":"Weisheng","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyu","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.aei.2026.104799_b0155","series-title":"Assessing the leanness of modular integrated construction (MiC) manufacturing: a non-intrusive scientific management approach","first-page":"1","author":"Lu","year":"2025"},{"key":"10.1016\/j.aei.2026.104799_b0050","article-title":"Modular construction: from projects to products","author":"Bertram","year":"2019","journal-title":"McKinsey & Company."},{"key":"10.1016\/j.aei.2026.104799_b0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.jobe.2021.102316","article-title":"Optimizing the modularization of floor plans in modular construction projects","volume":"39","author":"Almashaqbeh","year":"2021","journal-title":"Journal of Building Engineering"},{"key":"10.1016\/j.aei.2026.104799_b0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2021.104062","article-title":"BIM-based graph data model for automatic generative design of modular buildings","volume":"134","author":"Gan","year":"2022","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104799_b0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2023.105140","article-title":"An edge-weighted graph triumvirate to represent modular building layouts","volume":"157","author":"Lin","year":"2024","journal-title":"Autom. Constr."},{"issue":"1\u20132","key":"10.1016\/j.aei.2026.104799_b0150","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1080\/17452007.2020.1768505","article-title":"Design for manufacture and assembly (DfMA) in construction: the old and the new","volume":"17","author":"Lu","year":"2021","journal-title":"Architectural Engineering and Design Management"},{"key":"10.1016\/j.aei.2026.104799_b0195","series-title":"Prefab architecture: a guide to modular design and construction","author":"Smith","year":"2010"},{"issue":"2","key":"10.1016\/j.aei.2026.104799_b0200","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)AE.1943-5568.0000313","article-title":"Identification of factors and decision analysis of the level of modularization in building construction","volume":"24","author":"Sharafi","year":"2018","journal-title":"J. Archit. Eng."},{"issue":"6","key":"10.1016\/j.aei.2026.104799_b0160","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1108\/ECAM-04-2014-0048","article-title":"Risk factors affecting practitioners\u2019 attitudes toward the implementation of an industrialized building system: a case study from China","volume":"22","author":"Luo","year":"2015","journal-title":"Eng. Constr. Archit. Manag."},{"key":"10.1016\/j.aei.2026.104799_b0270","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.habitatint.2013.08.005","article-title":"Exploring the challenges to industrialized residential building in China","volume":"41","author":"Zhang","year":"2014","journal-title":"Habitat Int."},{"key":"10.1016\/j.aei.2026.104799_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.compind.2022.103659","article-title":"A graph-based approach for module library development in industrialized construction","volume":"139","author":"Cao","year":"2022","journal-title":"Comput. Ind."},{"key":"10.1016\/j.aei.2026.104799_b0260","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2019.100997","article-title":"An internet of Things-enabled BIM platform for modular integrated construction: a case study in Hong Kong","author":"Zhai","year":"2019","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104799_b0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2021.101514","article-title":"Feature modeling for configurable and adaptable modular buildings","volume":"51","author":"Benjamin","year":"2022","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104799_b0190","article-title":"Building information modelling, artificial intelligence and construction tech","volume":"4","author":"Sacks","year":"2020","journal-title":"Dev. Built Environ."},{"key":"10.1016\/j.aei.2026.104799_b0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2022.104234","article-title":"Automated modular housing design using a module configuration algorithm and a coupled generative adversarial network (CoGAN)","volume":"139","author":"Ghannad","year":"2022","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104799_b0230","series-title":"Introduction to graph theory","author":"West","year":"2001"},{"key":"10.1016\/j.aei.2026.104799_b0165","doi-asserted-by":"crossref","unstructured":"Nauata, N., Chang, K. H., Cheng, C. Y., Mori, G., & Furukawa, Y. (2020). House-gan: Relational generative adversarial networks for graph-constrained house layout generation. InComputer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part I 16(pp. 162-177). Springer International Publishing.","DOI":"10.1007\/978-3-030-58452-8_10"},{"issue":"4","key":"10.1016\/j.aei.2026.104799_b0120","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1145\/3386569.3392391","article-title":"Graph2plan: Learning floorplan generation from layout graphs","volume":"39","author":"Hu","year":"2020","journal-title":"ACM Transactions on Graphics (TOG)"},{"issue":"6","key":"10.1016\/j.aei.2026.104799_bib286","first-page":"1","article-title":"Data-driven interior plan generation for residential buildings","volume":"38","author":"Wu","year":"2019","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"10.1016\/j.aei.2026.104799_b0170","series-title":"In Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"6690","article-title":"Generative layout modeling using constraint graphs","author":"Para","year":"2021"},{"key":"10.1016\/j.aei.2026.104799_b0285","first-page":"1601","article-title":"Learning with hypergraphs: Clustering, classification, and embedding","volume":"19","author":"Zhou","year":"2007","journal-title":"Adv. Neural Inf. Proces. Syst."},{"issue":"01","key":"10.1016\/j.aei.2026.104799_b0085","doi-asserted-by":"crossref","first-page":"3558","DOI":"10.1609\/aaai.v33i01.33013558","article-title":"Hypergraph neural networks","volume":"33","author":"Feng","year":"2019","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"10.1016\/j.aei.2026.104799_b0250","first-page":"1511","article-title":"HyperGCN: a new method for training graph convolutional networks on hypergraphs","volume":"32","author":"Yadati","year":"2019","journal-title":"Adv. Neural Inf. Proces. Syst."},{"issue":"5","key":"10.1016\/j.aei.2026.104799_b0135","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1000385","article-title":"Hypergraphs and cellular networks","volume":"5","author":"Klamt","year":"2009","journal-title":"PLoS Comput. Biol."},{"issue":"48","key":"10.1016\/j.aei.2026.104799_b0045","doi-asserted-by":"crossref","first-page":"E11221","DOI":"10.1073\/pnas.1800683115","article-title":"Simplicial closure and higher-order link prediction","volume":"115","author":"Benson","year":"2018","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"4","key":"10.1016\/j.aei.2026.104799_b0280","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1007\/s11280-017-0494-5","article-title":"A novel social network hybrid recommender system based on hypergraph topologic structure","volume":"21","author":"Zheng","year":"2018","journal-title":"World Wide Web"},{"issue":"1","key":"10.1016\/j.aei.2026.104799_b0225","doi-asserted-by":"crossref","first-page":"8327","DOI":"10.1038\/s41467-024-52506-z","article-title":"A hypergraph model shows the carbon reduction potential of effective space use in housing","volume":"15","author":"Weber","year":"2024","journal-title":"Nat. Commun."},{"issue":"2","key":"10.1016\/j.aei.2026.104799_b0110","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1068\/b030147","article-title":"Space syntax","volume":"3","author":"Hillier","year":"1976","journal-title":"Environment and Planning b: Planning and Design"},{"key":"10.1016\/j.aei.2026.104799_b0205","doi-asserted-by":"crossref","DOI":"10.1016\/j.gmod.2023.101175","article-title":"Automated generation of floorplans with non-rectangular rooms","volume":"127","author":"Shekhawat","year":"2023","journal-title":"Graph. Model."},{"key":"10.1016\/j.aei.2026.104799_b0100","doi-asserted-by":"crossref","unstructured":"Gori, M., Monfardini, G., & Scarselli, F. (2005, July). A new model for learning in graph domains. In Proceedings. 2005 IEEE international joint conference on neural networks, 2005. (Vol. 2, pp. 729-734). IEEE.","DOI":"10.1109\/IJCNN.2005.1555942"},{"key":"10.1016\/j.aei.2026.104799_b0070","unstructured":"Bruna, J., Zaremba, W., Szlam, A., & LeCun, Y. (2014). Spectral networks and locally connected networks on graphs. arXiv preprint arXiv:1312.6203. DOI: 10.48550\/arXiv.1312.6203."},{"key":"10.1016\/j.aei.2026.104799_b0130","unstructured":"Kipf, T. N., & Welling, M. (2017). Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907. DOI: 10.48550\/arXiv.1609.02907."},{"issue":"1","key":"10.1016\/j.aei.2026.104799_b0245","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/TNNLS.2020.2978386","article-title":"A comprehensive survey on graph neural networks","volume":"32","author":"Wu","year":"2020","journal-title":"IEEE Trans. Neural Networks Learn. Syst."},{"key":"10.1016\/j.aei.2026.104799_b0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.jobe.2023.106378","article-title":"Floor plan recommendation system using graph neural network with spatial relationship dataset","volume":"71","author":"Park","year":"2023","journal-title":"Journal of Building Engineering"},{"key":"10.1016\/j.aei.2026.104799_b0220","article-title":"FB-GAT: a graph neural networks (GNNs) approach to assessing facades\u2019 buildability","volume":"69","author":"Wang","year":"2026","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104799_b0275","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.101886","article-title":"Intelligent design of shear wall layout based on graph neural networks","volume":"55","author":"Zhao","year":"2023","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104799_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102137","article-title":"Graph-based learning for automated code checking\u2013Exploring the application of graph neural networks for design review","volume":"58","author":"Bloch","year":"2023","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104799_b0180","series-title":"Routledge Handbook of Smart Built Environment","first-page":"35","article-title":"Generative Design for Excellence (DfX) for a Smart built Environment: from rule-based imitation to data-driven exploration","author":"Peng","year":"2025"},{"key":"10.1016\/j.aei.2026.104799_b0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2023.105053","article-title":"Architectural layout generation using a graph-constrained conditional Generative Adversarial Network (GAN)","volume":"155","author":"Aalaei","year":"2023","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104799_bib287","doi-asserted-by":"crossref","unstructured":"Van Engelenburg, C., Mostafavi, F., Kuhn, E., Jeon, Y., Franzen, M., Standfest, M., ... & Khademi, S. (2024, September). Msd: A benchmark dataset for floor plan generation of building complexes. In European Conference on Computer Vision (pp. 60-75). Cham: Springer Nature Switzerland.","DOI":"10.1007\/978-3-031-73636-0_4"},{"issue":"4","key":"10.1016\/j.aei.2026.104799_b0215","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3528223.3530135","article-title":"Wallplan: synthesizing floorplans by learning to generate wall graphs","volume":"41","author":"Sun","year":"2022","journal-title":"ACM Transactions on Graphics (TOG)"},{"issue":"8","key":"10.1016\/j.aei.2026.104799_b0080","doi-asserted-by":"crossref","DOI":"10.1061\/JCEMD4.COENG-14687","article-title":"Graph-based evolutionary search for optimal hybrid modularization of building construction projects","volume":"150","author":"Cao","year":"2024","journal-title":"J. Constr. Eng. Manag."},{"key":"10.1016\/j.aei.2026.104799_b0265","series-title":"InProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"793","article-title":"July). Heterogeneous graph neural network","author":"Zhang","year":"2019"},{"issue":"3","key":"10.1016\/j.aei.2026.104799_b0240","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1016\/j.ejor.2014.09.064","article-title":"A review on algorithms for maximum clique problems","volume":"242","author":"Wu","year":"2015","journal-title":"Eur. J. Oper. Res."},{"key":"10.1016\/j.aei.2026.104799_b0065","article-title":"Hypergraph theory: an introduction","author":"Bretto","year":"2013","journal-title":"Springer"},{"key":"10.1016\/j.aei.2026.104799_b0055","volume":"Vol. 45","author":"Berge","year":"1989"},{"issue":"1","key":"10.1016\/j.aei.2026.104799_b0020","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3605776","article-title":"A survey on hypergraph representation learning","volume":"56","author":"Antelmi","year":"2023","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.aei.2026.104799_b0025","volume":"Vol. 131","author":"Asratian","year":"1998"},{"key":"10.1016\/j.aei.2026.104799_b0255","series-title":"In Proceedings of the Tenth International Conference on Information and Knowledge Management","first-page":"25","article-title":"October). Bipartite graph partitioning and data clustering","author":"Zha","year":"2001"},{"key":"10.1016\/j.aei.2026.104799_b0125","doi-asserted-by":"crossref","first-page":"10797","DOI":"10.1109\/ACCESS.2026.3654644","article-title":"Revisiting Clique and Star Expansions in Hypergraph Representation Learning: Observations, Problems, and Solutions","volume":"14","author":"Kang","year":"2026","journal-title":"IEEE Access"},{"key":"10.1016\/j.aei.2026.104799_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2020.107637","article-title":"Hypergraph convolution and hypergraph attention","volume":"110","author":"Bai","year":"2021","journal-title":"Pattern Recogn."},{"issue":"4","key":"10.1016\/j.aei.2026.104799_b0210","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.aei.2009.06.007","article-title":"Reasoning about designs through frequent patterns mining","volume":"23","author":"Strug","year":"2009","journal-title":"Adv. Eng. Inf."},{"issue":"8","key":"10.1016\/j.aei.2026.104799_b0035","doi-asserted-by":"crossref","first-page":"1798","DOI":"10.1109\/TPAMI.2013.50","article-title":"Representation learning: a review and new perspectives","volume":"35","author":"Bengio","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.aei.2026.104799_b0105","unstructured":"Hamilton, W. L., Ying, R., & Leskovec, J. (2017). Representation learning on graphs: Methods and applications. arXiv preprint arXiv:1709.05584."},{"key":"10.1016\/j.aei.2026.104799_b0185","unstructured":"Pr Marion, B., Aksoy, S., Arendt, D., Bonicillo, M., Joslyn, C., Purvine, E., ... & Yun, J. Y. (2023). HyperNetX: A Python package for modeling complex network data as hypergraphs. arXiv preprint arXiv:2310.11626. DOI: 10.48550\/arXiv.2310.11626DOI: 10.48550\/arXiv.2310.11626."},{"key":"10.1016\/j.aei.2026.104799_bib288","unstructured":"Kingma, D. P., & Ba, J. (2014). Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980."},{"key":"10.1016\/j.aei.2026.104799_b0015","series-title":"A pattern language: towns, buildings, construction","author":"Alexander","year":"1977"},{"key":"10.1016\/j.aei.2026.104799_b0115","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.trpro.2020.03.187","article-title":"Optimal logistics planning for modular construction using multi-stage stochastic programming","volume":"46","author":"Hsu","year":"2020","journal-title":"Transp. Res. Procedia"},{"issue":"1","key":"10.1016\/j.aei.2026.104799_b0140","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.cad.2010.09.009","article-title":"A practical generative design method","volume":"43","author":"Krish","year":"2011","journal-title":"Comput. Aided Des."}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S147403462600491X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S147403462600491X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T10:22:31Z","timestamp":1783160551000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S147403462600491X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":59,"alternative-id":["S147403462600491X"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104799","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"HyperMB: A hypergraph representation and learning framework for modular building layout design decisions","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104799","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"104799"}}