Optimizing of the arrangement of the land uses is one of the main goals of urban land use planning. This issue involves a variety of spatial data and analyses. Moreover, existing different arrangements for diverse land uses causes in complex and wide search space. In view of these matters, the land use arrangement can be supposed as a spatial multi-objective optimization problem. In this research, Multi-Objective Particle Swarm Optimization algorithm along with GIS is applied in the seventh distinct of Tehran to find optimum arrangement of urban land uses. GIS is used to generate and analysis different scenarios of land use arrangements for the optimization algorithm. The proposed approach provides a variety of optimized solutions, giving the possibility of choosing the most desirable results to decision-makers. A new aspect of this research is using the land parcels as the spatial unit. In addition, making dynamic decision on the different types of land uses is one advantages of this method. The test of the method shows an acceptable level of implementation speed along with a high level of repeatability and stability of the algorithm. Keywords: Optimization, Land use planning, GIS, MOPSO, Multi-Objective, Micro Scale, Decision making.
(2016). Developing a Spatial Micro-scale Model for Optimum Arrangement of Urban Land Uses based on Multi-Objective Particle Swarm Optimization Algorithm. Iranian Journal of Remote Sensing & GIS, 7(1), 59-79.
MLA
. "Developing a Spatial Micro-scale Model for Optimum Arrangement of Urban Land Uses based on Multi-Objective Particle Swarm Optimization Algorithm". Iranian Journal of Remote Sensing & GIS, 7, 1, 2016, 59-79.
HARVARD
(2016). 'Developing a Spatial Micro-scale Model for Optimum Arrangement of Urban Land Uses based on Multi-Objective Particle Swarm Optimization Algorithm', Iranian Journal of Remote Sensing & GIS, 7(1), pp. 59-79.
VANCOUVER
Developing a Spatial Micro-scale Model for Optimum Arrangement of Urban Land Uses based on Multi-Objective Particle Swarm Optimization Algorithm. Iranian Journal of Remote Sensing & GIS, 2016; 7(1): 59-79.