Challenges in the green building supply chain: multi-objective planning for prefabricated factory site selection.
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| Title: | Challenges in the green building supply chain: multi-objective planning for prefabricated factory site selection. |
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| Authors: | Guo, Guihuan1,2 (AUTHOR) guoguihuan@whut.edu.cn, Wang, Junwu1,2 (AUTHOR) 267544@whut.edu.cn, Wanjin, Yingjun2 (AUTHOR) 300395@whut.edu.cn, Song, Yinghui2,3 (AUTHOR) songyinghui@whut.edu.cn |
| Source: | Environment, Development & Sustainability. Jul2026, Vol. 28 Issue 7, p16037-16079. 43p. |
| Subject Terms: | *Multi-objective optimization, *Carbon emissions, *Optimization algorithms, *Geoinformatics, *Sustainable development, *Supply chains, *Sustainable buildings |
| Geographic Terms: | China |
| Abstract: | In the context of the global trend towards promoting green development, the strategic selection of construction sites for prefabricated building component factories is crucial for the sustainable growth of businesses and aligns with environmental stewardship efforts, contributing to China's pursuit of "dual carbon" policy objectives. However, current research on the site selection of prefabricated component factories has several typical shortcomings. These include the absence of a comprehensive site selection index evaluation system, subjective qualitative analyses, excessive emphasis on economic benefits at the expense of environmental importance, and the limited accuracy of quantitative analysis tools. To address these issues, this study proposes a site selection evaluation system that considers both economic and environmental factors. Utilizing GIS analysis, the optimal candidate areas for prefabricated component factory site selection can be identified. Additionally, the improved GM (1,1) model is employed to forecast the demand for prefabricated components in the target area. Based on this forecast, a site selection objective function model is established to minimize total construction and transportation costs and carbon emissions. This study also introduces an improved NSGA-III algorithm (MBPSO-NSGA-III) for solving the site selection model. The optimal candidate sites for prefabricated component factories are then selected based on the site selection index evaluation system. The results of real case analyses show that employing this site selection model can lead to cost savings of about 15% or more and lower carbon dioxide emissions, support green development in the construction industry, boost enterprises' capacity for sustainable development, and achieve environmental responsibility objectives. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 194936931 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Challenges in the green building supply chain: multi-objective planning for prefabricated factory site selection. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Guo%2C+Guihuan%22">Guo, Guihuan</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> guoguihuan@whut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Junwu%22">Wang, Junwu</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> 267544@whut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wanjin%2C+Yingjun%22">Wanjin, Yingjun</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> 300395@whut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Song%2C+Yinghui%22">Song, Yinghui</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> songyinghui@whut.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Environment%2C+Development+%26+Sustainability%22">Environment, Development & Sustainability</searchLink>. Jul2026, Vol. 28 Issue 7, p16037-16079. 43p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Carbon+emissions%22">Carbon emissions</searchLink><br />*<searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Geoinformatics%22">Geoinformatics</searchLink><br />*<searchLink fieldCode="DE" term="%22Sustainable+development%22">Sustainable development</searchLink><br />*<searchLink fieldCode="DE" term="%22Supply+chains%22">Supply chains</searchLink><br />*<searchLink fieldCode="DE" term="%22Sustainable+buildings%22">Sustainable buildings</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In the context of the global trend towards promoting green development, the strategic selection of construction sites for prefabricated building component factories is crucial for the sustainable growth of businesses and aligns with environmental stewardship efforts, contributing to China's pursuit of "dual carbon" policy objectives. However, current research on the site selection of prefabricated component factories has several typical shortcomings. These include the absence of a comprehensive site selection index evaluation system, subjective qualitative analyses, excessive emphasis on economic benefits at the expense of environmental importance, and the limited accuracy of quantitative analysis tools. To address these issues, this study proposes a site selection evaluation system that considers both economic and environmental factors. Utilizing GIS analysis, the optimal candidate areas for prefabricated component factory site selection can be identified. Additionally, the improved GM (1,1) model is employed to forecast the demand for prefabricated components in the target area. Based on this forecast, a site selection objective function model is established to minimize total construction and transportation costs and carbon emissions. This study also introduces an improved NSGA-III algorithm (MBPSO-NSGA-III) for solving the site selection model. The optimal candidate sites for prefabricated component factories are then selected based on the site selection index evaluation system. The results of real case analyses show that employing this site selection model can lead to cost savings of about 15% or more and lower carbon dioxide emissions, support green development in the construction industry, boost enterprises' capacity for sustainable development, and achieve environmental responsibility objectives. [ABSTRACT FROM AUTHOR] |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10668-024-05491-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 43 StartPage: 16037 Subjects: – SubjectFull: Multi-objective optimization Type: general – SubjectFull: Carbon emissions Type: general – SubjectFull: Optimization algorithms Type: general – SubjectFull: Geoinformatics Type: general – SubjectFull: Sustainable development Type: general – SubjectFull: Supply chains Type: general – SubjectFull: Sustainable buildings Type: general – SubjectFull: China Type: general Titles: – TitleFull: Challenges in the green building supply chain: multi-objective planning for prefabricated factory site selection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Guo, Guihuan – PersonEntity: Name: NameFull: Wang, Junwu – PersonEntity: Name: NameFull: Wanjin, Yingjun – PersonEntity: Name: NameFull: Song, Yinghui IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 1387585X Numbering: – Type: volume Value: 28 – Type: issue Value: 7 Titles: – TitleFull: Environment, Development & Sustainability Type: main |
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