Optimization of multi-objective land use model with genetic algorithm
The first task of the city planner is to effectively locate integrated land use types for various objectives. The Multi Objective Land Use Planning Model developed to achieve this goal, aims to maximize land value and minimize the transportation. The genetic algorithm method developed to find the op...
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| Format: | Article |
| Language: | English |
| Published: |
Mehmet Topcu
2020-12-01
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| Series: | Journal of Design for Resilience in Architecture and Planning |
| Subjects: | |
| Online Access: | https://www.drarch.org/index.php/drarch/article/view/21 |
| _version_ | 1811161110201499648 |
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| author | Hasan Mutlu |
| author_facet | Hasan Mutlu |
| author_sort | Hasan Mutlu |
| collection | DOAJ |
| description | The first task of the city planner is to effectively locate integrated land use types for various objectives. The Multi Objective Land Use Planning Model developed to achieve this goal, aims to maximize land value and minimize the transportation. The genetic algorithm method developed to find the optimum layout according to the Multi-Objective Land Use Planning Model has been explained, the success and performance of the process has been tested with artificial data, and its usability in real problems has been examined. According to the results of the study, using this method, it is revealed that layout plans that are very close to the maximum efficiency value can be found within 1 day in cities with a population of up to 1,000,000, within 1 week in cities up to 5,000,000, and within 1.5 months in cities close to 16,000,000. By examining the results, the deficiencies of this method are determined and the suggestions for improvement of this method are stated. The problem chosen in this study is a problem that most city planners have to solve and the developed application has been opened to the use of other experts. This makes this work unique as it allows planning experts who are incapable of developing such methods to experiment. |
| first_indexed | 2024-04-10T06:09:11Z |
| format | Article |
| id | doaj.art-23dfffe30bad463ab0fea083ec6b5682 |
| institution | Directory Open Access Journal |
| issn | 2757-6329 |
| language | English |
| last_indexed | 2024-04-10T06:09:11Z |
| publishDate | 2020-12-01 |
| publisher | Mehmet Topcu |
| record_format | Article |
| series | Journal of Design for Resilience in Architecture and Planning |
| spelling | doaj.art-23dfffe30bad463ab0fea083ec6b56822023-03-02T20:24:38ZengMehmet TopcuJournal of Design for Resilience in Architecture and Planning2757-63292020-12-0111153210.47818/DRArch.2020.v1i100221Optimization of multi-objective land use model with genetic algorithmHasan Mutlu0https://orcid.org/0000-0001-9026-2773Urban Planner (M.Sc.)The first task of the city planner is to effectively locate integrated land use types for various objectives. The Multi Objective Land Use Planning Model developed to achieve this goal, aims to maximize land value and minimize the transportation. The genetic algorithm method developed to find the optimum layout according to the Multi-Objective Land Use Planning Model has been explained, the success and performance of the process has been tested with artificial data, and its usability in real problems has been examined. According to the results of the study, using this method, it is revealed that layout plans that are very close to the maximum efficiency value can be found within 1 day in cities with a population of up to 1,000,000, within 1 week in cities up to 5,000,000, and within 1.5 months in cities close to 16,000,000. By examining the results, the deficiencies of this method are determined and the suggestions for improvement of this method are stated. The problem chosen in this study is a problem that most city planners have to solve and the developed application has been opened to the use of other experts. This makes this work unique as it allows planning experts who are incapable of developing such methods to experiment.https://www.drarch.org/index.php/drarch/article/view/21spatial optimizationgenetic algorithmmulti objective land use planning |
| spellingShingle | Hasan Mutlu Optimization of multi-objective land use model with genetic algorithm Journal of Design for Resilience in Architecture and Planning spatial optimization genetic algorithm multi objective land use planning |
| title | Optimization of multi-objective land use model with genetic algorithm |
| title_full | Optimization of multi-objective land use model with genetic algorithm |
| title_fullStr | Optimization of multi-objective land use model with genetic algorithm |
| title_full_unstemmed | Optimization of multi-objective land use model with genetic algorithm |
| title_short | Optimization of multi-objective land use model with genetic algorithm |
| title_sort | optimization of multi objective land use model with genetic algorithm |
| topic | spatial optimization genetic algorithm multi objective land use planning |
| url | https://www.drarch.org/index.php/drarch/article/view/21 |
| work_keys_str_mv | AT hasanmutlu optimizationofmultiobjectivelandusemodelwithgeneticalgorithm |