Dynamic model averaging-based procurement optimization of prefabricated components

Du, J; Li, X; Sugumaran, V; Hu, Y; Xue, Y

Dynamic model averaging-based procurement optimization of prefabricated components

Du, J

Li, X Sugumaran, V Hu, Y Xue, Y

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Publisher:: SPRINGER LONDON LTD
Publication Type:: Journal Article
Citation:: Neural Computing and Applications, 2023, 35, (36), pp. 25157-25173
Issue Date:: 2023-12-01

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Field	Value	Language
dc.contributor.author	Du, J https://orcid.org/0000-0002-6428-7763
dc.contributor.author	Li, X
dc.contributor.author	Sugumaran, V
dc.contributor.author	Hu, Y
dc.contributor.author	Xue, Y
dc.date.accessioned	2024-02-05T21:55:49Z
dc.date.available	2024-02-05T21:55:49Z
dc.date.issued	2023-12-01
dc.identifier.citation	Neural Computing and Applications, 2023, 35, (36), pp. 25157-25173
dc.identifier.issn	0941-0643
dc.identifier.issn	1433-3058
dc.identifier.uri	http://hdl.handle.net/10453/175323
dc.description.abstract	With the promotion of construction industrialization, the prefabricated construction market is becoming increasingly competitive. The raw material cost of prefabricated components accounts for a large proportion of the total cost of prefabricated construction project. Effective planning of raw material procurement strategy for prefabricated components can significantly optimize the cost of materials and prefabricated construction project. Considering the impact of material price fluctuation and demand change on the procurement strategy of raw materials for prefabricated components, this study proposes a procurement model of raw materials for prefabricated components, which considers the changing demand and price fluctuation under multiple time series. Firstly, the price of raw materials for prefabricated components is predicted based on dynamic model averaging and dynamic model selection, and then, price is embedded into the procurement and inventory replenishment model. Finally, the raw material procurement strategy with the objective of minimizing procurement cost is generated through genetic algorithm. An application example is presented to demonstrate the capabilities of the procurement strategy model with respect to accuracy of price prediction and optimizing material procurement decisions.
dc.language	English
dc.publisher	SPRINGER LONDON LTD
dc.relation.ispartof	Neural Computing and Applications
dc.relation.isbasedon	10.1007/s00521-023-08715-6
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0906 Electrical and Electronic Engineering, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4603 Computer vision and multimedia computation
dc.subject.classification	4611 Machine learning
dc.title	Dynamic model averaging-based procurement optimization of prefabricated components
dc.type	Journal Article
utslib.citation.volume	35
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Professional Practice and Leadership
utslib.copyright.status	closed_access	*
dc.date.updated	2024-02-05T21:55:47Z
pubs.issue	36
pubs.publication-status	Published
pubs.volume	35
utslib.citation.issue	36

Abstract:

With the promotion of construction industrialization, the prefabricated construction market is becoming increasingly competitive. The raw material cost of prefabricated components accounts for a large proportion of the total cost of prefabricated construction project. Effective planning of raw material procurement strategy for prefabricated components can significantly optimize the cost of materials and prefabricated construction project. Considering the impact of material price fluctuation and demand change on the procurement strategy of raw materials for prefabricated components, this study proposes a procurement model of raw materials for prefabricated components, which considers the changing demand and price fluctuation under multiple time series. Firstly, the price of raw materials for prefabricated components is predicted based on dynamic model averaging and dynamic model selection, and then, price is embedded into the procurement and inventory replenishment model. Finally, the raw material procurement strategy with the objective of minimizing procurement cost is generated through genetic algorithm. An application example is presented to demonstrate the capabilities of the procurement strategy model with respect to accuracy of price prediction and optimizing material procurement decisions.

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http://hdl.handle.net/10453/175323