Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm
A multi-objective optimization method based on the improved non-dominated sorting genetic algorithm II was proposed to address the problem of spatial layout optimization in urban renewal. The study first constructed an urban spatial layout model with net zero carbon as the core concept, setting thre...
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MDPI AG
2024-12-01
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| author | Xuan Han Baishu Xia |
| author_facet | Xuan Han Baishu Xia |
| author_sort | Xuan Han |
| collection | DOAJ |
| description | A multi-objective optimization method based on the improved non-dominated sorting genetic algorithm II was proposed to address the problem of spatial layout optimization in urban renewal. The study first constructed an urban spatial layout model with net zero carbon as the core concept, setting three optimization objectives: minimizing net carbon emissions, maximizing regional GDP, and compact utilization of land functions. By introducing the Non-dominated Sorting Genetic Algorithm II for multi-objective optimization of the solution, this algorithm uses fitness non-dominated sorting and crowding distance calculation to maintain population diversity and combined the approximate ideal solution sorting method to improve convergence. The experiment outcomes indicate that the raised algorithm achieves an optimization result of 5.79 × 10<sup>−20</sup> in the Rastrigin function and exhibits better uniformity in the distribution of solution values in the ZDT1 function. In terms of urban spatial layout, the optimized scheme has a net carbon emission of 19,821.80 tons, a regional GDP of 2.342367 billion USD, and a compact land function of 5791.93, indicating that the scheme not only effectively controls carbon emissions but also demonstrates the rationality and sustainability of land resource use. |
| format | Article |
| id | doaj-art-178bf5cc569c43aeb329898ebd0fa01a |
| institution | Kabale University |
| issn | 2075-5309 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Buildings |
| spelling | doaj-art-178bf5cc569c43aeb329898ebd0fa01a2025-01-10T13:16:01ZengMDPI AGBuildings2075-53092024-12-011519410.3390/buildings15010094Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII AlgorithmXuan Han0Baishu Xia1School of Architecture and Planning, Shenyang Jianzhu University, Shenyang 110168, ChinaSchool of Architecture and Planning, Shenyang Jianzhu University, Shenyang 110168, ChinaA multi-objective optimization method based on the improved non-dominated sorting genetic algorithm II was proposed to address the problem of spatial layout optimization in urban renewal. The study first constructed an urban spatial layout model with net zero carbon as the core concept, setting three optimization objectives: minimizing net carbon emissions, maximizing regional GDP, and compact utilization of land functions. By introducing the Non-dominated Sorting Genetic Algorithm II for multi-objective optimization of the solution, this algorithm uses fitness non-dominated sorting and crowding distance calculation to maintain population diversity and combined the approximate ideal solution sorting method to improve convergence. The experiment outcomes indicate that the raised algorithm achieves an optimization result of 5.79 × 10<sup>−20</sup> in the Rastrigin function and exhibits better uniformity in the distribution of solution values in the ZDT1 function. In terms of urban spatial layout, the optimized scheme has a net carbon emission of 19,821.80 tons, a regional GDP of 2.342367 billion USD, and a compact land function of 5791.93, indicating that the scheme not only effectively controls carbon emissions but also demonstrates the rationality and sustainability of land resource use.https://www.mdpi.com/2075-5309/15/1/94NSGA-IIapproximate ideal solution sorting methodnet zero carbonspatial distribution |
| spellingShingle | Xuan Han Baishu Xia Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm Buildings NSGA-II approximate ideal solution sorting method net zero carbon spatial distribution |
| title | Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm |
| title_full | Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm |
| title_fullStr | Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm |
| title_full_unstemmed | Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm |
| title_short | Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm |
| title_sort | spatial layout optimization in urban renewal based on improved nsgaii algorithm |
| topic | NSGA-II approximate ideal solution sorting method net zero carbon spatial distribution |
| url | https://www.mdpi.com/2075-5309/15/1/94 |
| work_keys_str_mv | AT xuanhan spatiallayoutoptimizationinurbanrenewalbasedonimprovednsgaiialgorithm AT baishuxia spatiallayoutoptimizationinurbanrenewalbasedonimprovednsgaiialgorithm |