Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example
Effective planning of logistics land is crucial for mitigating urban freight congestion, fostering economic activities, and achieving environmental equilibrium. However, the dual challenge of mismatched logistics supply and demand, along with conflicts in land use functions, can lead to inefficienci...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2024.2449568 |
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| author | Hongzan Jiao Shuaikang Zhang |
| author_facet | Hongzan Jiao Shuaikang Zhang |
| author_sort | Hongzan Jiao |
| collection | DOAJ |
| description | Effective planning of logistics land is crucial for mitigating urban freight congestion, fostering economic activities, and achieving environmental equilibrium. However, the dual challenge of mismatched logistics supply and demand, along with conflicts in land use functions, can lead to inefficiencies in resource allocation and urban freight system performance. To tackle this issue, our study integrates truck GPS trajectory data with urban land use datasets to formulate a multi-objective optimization model. By utilizing the gradient descent algorithm, which effectively handles large-scale datasets, we can navigate the complexities of logistics land planning with precision. The application of this model in the Wuhan Urban Development Area reveals that: (1) across various scenarios, the model balances the utilization of multiple optimization objectives and demonstrates high solution efficiency; (2) in both the equal weight scenario and the economic preference scenario, the areas of logistics land change are characterized by high economic output, relatively good traffic conditions, greater distance from residential zones, and comparatively low land prices; and (3) based on urban development goals, the model can determine the upper bounds of the optimization objectives through manual supervision of the selection of ideal points. |
| format | Article |
| id | doaj-art-11e2325da73148edb3f474b1b594c642 |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-11e2325da73148edb3f474b1b594c6422025-01-13T01:24:04ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-12-0118110.1080/17538947.2024.2449568Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an exampleHongzan Jiao0Shuaikang Zhang1Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan, People’s Republic of ChinaDepartment of Urban Planning, School of Urban Design, Wuhan University, Wuhan, People’s Republic of ChinaEffective planning of logistics land is crucial for mitigating urban freight congestion, fostering economic activities, and achieving environmental equilibrium. However, the dual challenge of mismatched logistics supply and demand, along with conflicts in land use functions, can lead to inefficiencies in resource allocation and urban freight system performance. To tackle this issue, our study integrates truck GPS trajectory data with urban land use datasets to formulate a multi-objective optimization model. By utilizing the gradient descent algorithm, which effectively handles large-scale datasets, we can navigate the complexities of logistics land planning with precision. The application of this model in the Wuhan Urban Development Area reveals that: (1) across various scenarios, the model balances the utilization of multiple optimization objectives and demonstrates high solution efficiency; (2) in both the equal weight scenario and the economic preference scenario, the areas of logistics land change are characterized by high economic output, relatively good traffic conditions, greater distance from residential zones, and comparatively low land prices; and (3) based on urban development goals, the model can determine the upper bounds of the optimization objectives through manual supervision of the selection of ideal points.https://www.tandfonline.com/doi/10.1080/17538947.2024.2449568Logistics landmulti-objective optimizationgradient descent methodtruck GPS trajectory dataWuhan urban development zone |
| spellingShingle | Hongzan Jiao Shuaikang Zhang Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example International Journal of Digital Earth Logistics land multi-objective optimization gradient descent method truck GPS trajectory data Wuhan urban development zone |
| title | Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example |
| title_full | Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example |
| title_fullStr | Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example |
| title_full_unstemmed | Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example |
| title_short | Multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example |
| title_sort | multi objective optimization of urban logistics land a gradient based method approach with wuhan city as an example |
| topic | Logistics land multi-objective optimization gradient descent method truck GPS trajectory data Wuhan urban development zone |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2024.2449568 |
| work_keys_str_mv | AT hongzanjiao multiobjectiveoptimizationofurbanlogisticslandagradientbasedmethodapproachwithwuhancityasanexample AT shuaikangzhang multiobjectiveoptimizationofurbanlogisticslandagradientbasedmethodapproachwithwuhancityasanexample |