LOGISTICS-DRIVEN RETAIL CLUSTERING FOR OPTIMAL URBAN CONSOLIDATION CENTER PLACEMENT.
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| Title: | LOGISTICS-DRIVEN RETAIL CLUSTERING FOR OPTIMAL URBAN CONSOLIDATION CENTER PLACEMENT. |
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| Authors: | VASS, Lívia1 livijudo03@gmail.com, BÁNYAI, Tamás1 tamas.banyai@uni-miskolc.hu |
| Source: | Academic Journal of Manufacturing Engineering. 2025, Vol. 23 Issue 4, p98-118. 21p. |
| Subjects: | Delivery of goods, Mathematical models, Warehouses, Freight & freightage, Python programming language |
| Abstract: | Urban freight transport is vital for city logistics but also contributes to congestion and environmental issues. Urban Consolidation Centers (UCCs) offer a promising way to streamline last-mile deliveries and reduce these impacts. This research aims to determine the optimal location for UCCs by first identifying clusters of retail stores within an urban area. These clusters form the basis for selecting the most suitable UCC sites. The research includes defining clustering criteria for logistics optimization, developing related mathematical models, creating a real-data-based case study, coding the method in Python, selecting UCCs based on clusters, and evaluating the clustering criteria. The findings will support more efficient and sustainable urban logistics. [ABSTRACT FROM AUTHOR] |
| Copyright of Academic Journal of Manufacturing Engineering is the property of Academic Association for Manufacturing Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 190811488 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: LOGISTICS-DRIVEN RETAIL CLUSTERING FOR OPTIMAL URBAN CONSOLIDATION CENTER PLACEMENT. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22VASS%2C+Lívia%22">VASS, Lívia</searchLink><relatesTo>1</relatesTo><i> livijudo03@gmail.com</i><br /><searchLink fieldCode="AR" term="%22BÁNYAI%2C+Tamás%22">BÁNYAI, Tamás</searchLink><relatesTo>1</relatesTo><i> tamas.banyai@uni-miskolc.hu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Academic+Journal+of+Manufacturing+Engineering%22">Academic Journal of Manufacturing Engineering</searchLink>. 2025, Vol. 23 Issue 4, p98-118. 21p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Delivery+of+goods%22">Delivery of goods</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Warehouses%22">Warehouses</searchLink><br /><searchLink fieldCode="DE" term="%22Freight+%26+freightage%22">Freight & freightage</searchLink><br /><searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Urban freight transport is vital for city logistics but also contributes to congestion and environmental issues. Urban Consolidation Centers (UCCs) offer a promising way to streamline last-mile deliveries and reduce these impacts. This research aims to determine the optimal location for UCCs by first identifying clusters of retail stores within an urban area. These clusters form the basis for selecting the most suitable UCC sites. The research includes defining clustering criteria for logistics optimization, developing related mathematical models, creating a real-data-based case study, coding the method in Python, selecting UCCs based on clusters, and evaluating the clustering criteria. The findings will support more efficient and sustainable urban logistics. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Academic Journal of Manufacturing Engineering is the property of Academic Association for Manufacturing Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5281/zenodo.17937955 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 98 Subjects: – SubjectFull: Delivery of goods Type: general – SubjectFull: Mathematical models Type: general – SubjectFull: Warehouses Type: general – SubjectFull: Freight & freightage Type: general – SubjectFull: Python programming language Type: general Titles: – TitleFull: LOGISTICS-DRIVEN RETAIL CLUSTERING FOR OPTIMAL URBAN CONSOLIDATION CENTER PLACEMENT. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: VASS, Lívia – PersonEntity: Name: NameFull: BÁNYAI, Tamás IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 15837904 Numbering: – Type: volume Value: 23 – Type: issue Value: 4 Titles: – TitleFull: Academic Journal of Manufacturing Engineering Type: main |
| ResultId | 1 |
