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Sustainability 2015, 7(11), 15632-15651; doi:10.3390/su71115632

Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editor: Vincenzo Torretta
Received: 15 October 2015 / Revised: 16 November 2015 / Accepted: 17 November 2015 / Published: 23 November 2015
(This article belongs to the Section Sustainable Use of the Environment and Resources)
View Full-Text   |   Download PDF [1623 KB, uploaded 23 November 2015]   |  


As the main feature of land use planning, land use allocation (LUA) optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA optimization is a multi-objective optimization problem under the land use supply and demand constraints in a region. In order to obtain a better sustainable multi-objective LUA optimization solution, the present study proposes a LUA model based on the multi-objective artificial immune optimization algorithm (MOAIM-LUA model). The main achievements of the present study are as follows: (a) the land-use supply and demand factors are analyzed and the constraint conditions of LUA optimization problems are constructed based on the analysis framework of the balance between the land use supply and demand; (b) the optimization objectives of LUA optimization problems are defined and modeled using ecosystem service value theory and land rent and price theory; and (c) a multi-objective optimization algorithm is designed for solving multi-objective LUA optimization problems based on the novel immune clonal algorithm (NICA). On the basis of the aforementioned achievements, MOAIM-LUA was applied to a real case study of land-use planning in Anlu County, China. Compared to the current land use situation in Anlu County, optimized LUA solutions offer improvements in the social and ecological objective areas. Compared to the existing models, such as the non-dominated sorting genetic algorithm-II, experimental results demonstrate that the model designed in the present study can obtain better non-dominated solution sets and is superior in terms of algorithm stability. View Full-Text
Keywords: land use planning; land use allocation; multi-objective optimization land use planning; land use allocation; multi-objective optimization

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ma, X.; Zhao, X. Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China. Sustainability 2015, 7, 15632-15651.

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