scholarly journals Urban Land-Use Allocation By A Cell-based Multi-Objective Optimization Algorithm

2019 ◽  
Vol 6 (4) ◽  
pp. 163-186
Author(s):  
Jamshid Maleki ◽  
Farshad Hakimpour ◽  
Zohreh Masoumi ◽  
◽  
◽  
...  
2019 ◽  
Vol 24 (6) ◽  
pp. 4165-4190
Author(s):  
Zohreh Masoumi ◽  
Carlos A. Coello Coello ◽  
Ali Mansourian

Author(s):  
Mehran Shaygan ◽  
Abbas Alimohammadi ◽  
Ali Mansourian ◽  
Zohreh Shams Govara ◽  
S. Mostapha Kalami

Author(s):  
Y. Zeng ◽  
W. Huang ◽  
W. Jin ◽  
S. Li

The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.


Author(s):  
Y. Zeng ◽  
W. Huang ◽  
W. Jin ◽  
S. Li

The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.


2019 ◽  
Vol 118 ◽  
pp. 241-251 ◽  
Author(s):  
Michael Strauch ◽  
Anna F. Cord ◽  
Carola Pätzold ◽  
Sven Lautenbach ◽  
Andrea Kaim ◽  
...  

2016 ◽  
Vol 44 (1) ◽  
pp. 54-79 ◽  
Author(s):  
Shukui Tan ◽  
Lu Zhang ◽  
Min Zhou ◽  
Yanan Li ◽  
Siliang Wang ◽  
...  

Various uncertainties exist in most urban land-use allocation systems; however, they have not been considered in most traditional urban land-use allocation methods. In this study, an interval-probabilistic urban land-use allocation model is developed based on a hybrid interval-probabilistic programming method. The developed interval-probabilistic urban land-use allocation model can deal with uncertainties expressed as intervals and probability distributions; moreover, it can also help examine the reliability of satisfying (or risk of violating) system constraints under uncertainty; the interval-probabilistic urban land-use allocation model not only considers economic factors, but also involves environmental and ecological constraints, which can effectively reflect various interrelations among different aspects in the urban land-use system. The developed model is applied to a case of long-term land-use allocation planning in the city of Wuhan, China. Interval solutions associated with different risk levels of constraint violation are obtained. The desired system benefit from the land-use system will be between $ [1781.921, 2290.970] × 109 under the minimum violating probabilities, and in this condition, the optimized areas of industrial land, commercial land and landfill will be [35,739, 42,402] ha, [58,572, 62,450] ha, and [903, 1087] ha. Results provide the decision makers of Wuhan with desired land-use allocation patterns and environmental policies, which are related to a variety of trade-offs between system benefit and constraint-violation risk. Willingness to accept low benefit from land-use system will guarantee meeting the environmental protection objective. A strong desire to acquire high system benefit will run into the risk of violating environmental constraint.


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