Publication Type
Journal Article
Version
publishedVersion
Publication Date
1-2020
Abstract
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.
Keywords
Accessibility, Boundary-based genetic algorithm, Livability, Singapore, Smart planning, Spatial multi-objective land use optimization
Discipline
Asian Studies | Geographic Information Sciences | Theory and Algorithms | Urban Studies and Planning
Research Areas
Data Science and Engineering
Publication
ISPRS International Journal of Geo-Information
Volume
9
Issue
1
First Page
1
Last Page
18
ISSN
2220-9964
Identifier
10.3390/ijgi9010040
Publisher
MDPI
Citation
CAO, Kai; LIU, Muyang; WANG, Shu; LIU, Mengqi; ZHANG, Wenting; MENG, Qiang; and HUANG, Bo.
Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore. (2020). ISPRS International Journal of Geo-Information. 9, (1), 1-18.
Available at: https://ink.library.smu.edu.sg/sis_research/5119
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.3390/ijgi9010040
Included in
Asian Studies Commons, Geographic Information Sciences Commons, Theory and Algorithms Commons, Urban Studies and Planning Commons