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:: Volume 6, Issue 4 (3-2019) ::
jgit 2019, 6(4): 163-186 Back to browse issues page
Urban Land-Use Allocation By A Cell-based Multi-Objective Optimization Algorithm
Jamshid Maleki , Farshad Hakimpour , Zohreh Masoumi *
University in Advanced Studies in Basic Sciences
Abstract:   (3112 Views)
Allocating urban land-uses to land-units with regard to different criteria and constraints is considered as a spatial multi-objective problem. Generating various urban land-use layouts with respect to defined objectives for urban land-use allocation can support urban planners in confirming appropriate layouts. Hence, in this research, a multi-objective optimization algorithm based on grid is proposed to generate well-distributed solutions in objective space. In order to preserve diversity in Pareto front approximation, a grid is defined in objective space. The cells of this grid cluster the solutions and determine the suitable solutions for next generation in optimization process. The land-uses of region 1 of the district 7 of Tehran is used to assess the efficiency of the algorithm in optimizing urban land-use allocation. The results of the proposed algorithm are compared with the results of Non-dominated Sorting Genetic Algorithm II and III (NSGA-II and NSGA-III). Comparing the results indicate that the proposed algorithm acts better than NSGA-II and NSGA-III in preserving diversity and improving the convergence of the solutions in Pareto front.
Keywords: Urban Land-use Allocation, Grid-based NSGA-II, Multi-objective Optimization, Spatial Planning Support Systems.
Full-Text [PDF 2063 kb]   (1071 Downloads)    
Type of Study: Research | Subject: GIS
Received: 2017/10/15 | Accepted: 2018/06/10 | Published: 2019/03/20
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Maleki J, Hakimpour F, Masoumi Z. Urban Land-Use Allocation By A Cell-based Multi-Objective Optimization Algorithm. jgit 2019; 6 (4) :163-186
URL: http://jgit.kntu.ac.ir/article-1-650-en.html


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Volume 6, Issue 4 (3-2019) Back to browse issues page
نشریه علمی-پژوهشی مهندسی فناوری اطلاعات مکانی Engineering Journal of Geospatial Information Technology
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