Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore
In this research, the concept of livability has been quantitatively and comprehensively reviewed and interpreted to contribute to spatial multi-objective land use optimization modelling. In addition, a multi-objective land use optimization model was constructed using goal programming and a weighted-...
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sg-smu-ink.sis_research-61222023-10-30T07:02:21Z Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore CAO, Kai LIU, Muyang WANG, Shu LIU, Mengqi ZHANG, Wenting MENG, Qiang HUANG, Bo In this research, the concept of livability has been quantitatively and comprehensively reviewed and interpreted to contribute to spatial multi-objective land use optimization modelling. In addition, a multi-objective land use optimization model was constructed using goal programming and a weighted-sum approach, followed by a boundary-based genetic algorithm adapted to help address the spatial multi-objective land use optimization problem. Furthermore, the model is successfully and effectively applied to the case study in the Central Region of Queenstown Planning Area of Singapore towards livability. In the case study, the experiments based on equal weights and experiments based on different weights combination have been successfully conducted, which can demonstrate the effectiveness of the spatial multi-objective land use optimization model developed in this research as well as the robustness and reliability of computer-generated solutions. In addition, the comparison between the computer-generated solutions and the two real planned scenarios has also clearly demonstrated that our generated solutions are much better in terms of fitness values. Lastly, the limitation and future direction of this research have been discussed. 2020-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5119 info:doi/10.3390/ijgi9010040 https://ink.library.smu.edu.sg/context/sis_research/article/6122/viewcontent/Spatial_Multi_Objective_Land_Use_Optimization_towa.pdf http://creativecommons.org/licenses/by/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Accessibility Boundary-based genetic algorithm Livability Singapore Smart planning Spatial multi-objective land use optimization Asian Studies Geographic Information Sciences Theory and Algorithms Urban Studies and Planning |
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Accessibility Boundary-based genetic algorithm Livability Singapore Smart planning Spatial multi-objective land use optimization Asian Studies Geographic Information Sciences Theory and Algorithms Urban Studies and Planning CAO, Kai LIU, Muyang WANG, Shu LIU, Mengqi ZHANG, Wenting MENG, Qiang HUANG, Bo Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore |
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In this research, the concept of livability has been quantitatively and comprehensively reviewed and interpreted to contribute to spatial multi-objective land use optimization modelling. In addition, a multi-objective land use optimization model was constructed using goal programming and a weighted-sum approach, followed by a boundary-based genetic algorithm adapted to help address the spatial multi-objective land use optimization problem. Furthermore, the model is successfully and effectively applied to the case study in the Central Region of Queenstown Planning Area of Singapore towards livability. In the case study, the experiments based on equal weights and experiments based on different weights combination have been successfully conducted, which can demonstrate the effectiveness of the spatial multi-objective land use optimization model developed in this research as well as the robustness and reliability of computer-generated solutions. In addition, the comparison between the computer-generated solutions and the two real planned scenarios has also clearly demonstrated that our generated solutions are much better in terms of fitness values. Lastly, the limitation and future direction of this research have been discussed. |
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CAO, Kai LIU, Muyang WANG, Shu LIU, Mengqi ZHANG, Wenting MENG, Qiang HUANG, Bo |
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CAO, Kai LIU, Muyang WANG, Shu LIU, Mengqi ZHANG, Wenting MENG, Qiang HUANG, Bo |
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CAO, Kai |
title |
Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore |
title_short |
Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore |
title_full |
Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore |
title_fullStr |
Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore |
title_full_unstemmed |
Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore |
title_sort |
spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: a case study in singapore |
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Institutional Knowledge at Singapore Management University |
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2020 |
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https://ink.library.smu.edu.sg/sis_research/5119 https://ink.library.smu.edu.sg/context/sis_research/article/6122/viewcontent/Spatial_Multi_Objective_Land_Use_Optimization_towa.pdf |
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